Wednesday, August 31, 2022

Case Study - Frederick Taylor's Industrial Engineering Department for Process Improvement for Productivity Increase - 1885


Based on Frederick Taylor's Piece Rate System - 1895 - Part 3



Frederick Taylor established the first department in factory doing industrial engineering work of process improvement for increase in productivity and cost reduction. The name he gave it to the department is "Elementary Rate Fixing."  Its function is to breakdown the process into elements and find the best way of doing each element  by observing number of persons doing the same element and finding the best way through time study. The next step is to find science behind the way of doing the elements. Then from the best ways of doing each element, a new process is developed and the operators are trained in it. The final step of rate fixing refers to specifying the time required to do each element and the piece rate for it. The Piece rate of a component is fixed by first developing the detail at element level. The operators are provided the instruction sheet at the element level so that they know the time specified for each element and make effort to do it in that time. Taylor stated that operators are motivated to do well when they know the goal clearly and receive feedback quickly. The elementary rate fixing department has the responsibility to develop productivity science, do productivity engineering and do productivity management.

Based on the statements of Taylor, we can say elementary rate fixing department was established in 1885 by Taylor at Midvale Steel.



35. When we recognize the real antagonism that exists between the interests of the men and their employers under all of the systems of piece-work* in common use, and when we remember the apparently irreconcilable conflict implied in the fundamental and perfectly legitimate aims of the two, namely, on the part of the men, —

THE UNIVERSAL DESIRE TO RECEIVE THE LARGEST  POSSIBLE WAGES FOR THEIR TIME ;

And on the part of the employers, —

THE DESIRE TO RECEIVE THE LARGEST POSSIBLE RETURN FOR THE WAGES PAID ;

What wonder that most of us arrive at the conclusion that no system of piece-work can be devised which will enable the two to cooperate without antagonism, and to their mutual benefit?

36. Yet it is the opinion of the writer that the system  which harmonizes the interests of the two and becomes the basis for harmonious cooperation lies must be based on the two following facts :

First . That the workmen in nearly every trade can and will materially increase their present output per day, providing they are assured of a permanent and larger return for their time than they have heretofore received.

Second. That the employers can well afford to pay higher wages per piece even permanently, providing each man and machine in the establishment turns out a proportionately larger amount of work (gives more productivity.

37. The truth of the latter statement arises from the well recognized fact that, in most lines of manufacture, the indirect expenses equal or exceed the wages paid directly to the workmen, and that these expenses remain approximately constant, whether the output of the establishment is great or small.

From this it follows that it is always cheaper to pay higher wages to the workmen when the output is proportionately increased : the diminution in the indirect portion of the cost per piece being greater than the increase in wages. Many manufacturers, in considering the cost of production, fail to realize the effect that the volume of output has on the cost. They lose sight of the fact that taxes, insurance, depreciation, rent, interest, salaries, office expenses, miscellaneous labor, sales expenses, and frequently the cost of power (which in the aggregate amount to as much as wages paid to workmen), remain about the same whether the output of the establishment is great or small.

38. In our endeavor to solve the piece-work problem by the application of the two fundamental facts above referred to, let us consider the obstacles in the path of harmonious cooperation, and suggest a method for their removal.

39. The most formidable obstacle is the lack of knowledge on the part of both the men and the management (but chiefly the latter) of the quickest time in which each piece of work can be done; or, briefly, the lack of accurate time-tables for the work of the place.

40. The remedy for this trouble lies in the establishment in every factory of a proper rate-fixing department; a department which shall have equal dignity and command equal respect with the engineering and managing departments, which shall be organized and conducted in an equally scientific and practical manner.

41. The rate-fixing, as at present conducted, even in our best managed establishments, is very similar to the mechanical engineering of fifty or sixty years ago. Mechanical engineering at that time consisted in imitating machines which were in more or less successful use, or in guessing at the dimensions and strength of the parts of a new machine ; and as the parts broke down or gave out, in replacing them with the stronger ones. Thus each new machine presented a problem almost independent of former designs, and one which could only be solved by months or years of practical experience and a series of break-downs.

Modern engineering, however, has become a study, not of individual machines, but of the resistance of materials, the fundamental principles of mechanics, and of the elements of design.

42. On the other hand, the ordinary rate-fixing (even the best of it), like the old-style engineering, is done by a foreman or superintendent who, with the aid of a clerk, looks over the record of the time in which a whole job was done as nearly like the new one as can be found, and then guesses at the time required to do the new job. No attempt is made to analyze and time each of the classes of work, or elements of which a job is composed ; although it is a far simpler task to resolve each job into its elements, to make a careful study of the quickest time in which each of the elementary operations can be done, and then to properly classify, tabulate, and index this information, and use it when required for rate-fixing, than it is to fix rates, with even an approximation to justice, under the common system of guessing.

43. In fact, it has never occurred to most superintendents that the work of their establishments consists of various combinations of elementary operations which can be timed in this way ; and a suggestion that this is a practical way of dealing with the piece-work problem usually meets with derision, or, at the best, with the answer that “ It might do for some simple business, but my work is entirely too complicated.”

44. This elementary system of fixing rates has been in successful operation for the past ten years, on work complicated in its nature and covering almost as wide a range of variety as any manufacturing that the writer knows of. In 1883, while foreman of the machine shop of the Midvale Steel Company of Philadelphia, it occurred to the writer that it was simpler to time each of the elements of the various kinds of work done in the place, and then find the quickest time in which each job could be done, by summing up the total times of its component parts, than it was to search through the records of former jobs and guess at the proper price. After practising this method of rate-fixing himself for about a year as well as circumstances would permit, it became evident that the system was a success. The writer then established the rate-fixing department, which has given out piece-work prices in the place ever since.

45. This department far more than paid for itself from the very start ; but it was several years before the full benefits of the system were felt, owing to the fact that the best methods of making and recording time observations of work done by the men, as well as of determining the maximum capacity of each of the machines in the place, and of making working-tables and time-tables, were not at first adopted.


Foot Note

1 The writer’s knowledge of the speed attained in the manufacture of textile goods is very limited. It is his opinion, however, that owing to the comparative uniformity of this class of work, and the
enormous number of machines and men engaged on similar operations, the maximum output per man and machine is more nearly realized in this class of manufactures than in any other. If this is the
case, the opportunity for improvement does not exist to the same extent here as in other trades. Some illustrations of the possible increase in the daily output of men and machines are given in paragraphs 78 to 82.


Subsequent events.

Taylor became a management consultant in 1893.
1895. He employed Sanford E. Thompson who developed slide rules for machine tool cutting parameters calculation and developed time study tools.
1897 - He introduced functional foremanship in Simonds Rolling Machine Company. Started formal planning department.
1898 - Consultancy assignment in Bethlehem Steel. Russell Davenport now in Bethlehem, former boss of Taylor at Midvale was instrumental in Taylor getting that consultancy assignment. Taylor started the assignment in April 1898.
1901 - Gantt's liberal approach in machine shop of Bethlehem. Task and Bonus system.
Source: Taylorism and the Workers at Bethlehem Steel, 1898-1901
Daniel Nelson
The Pennsylvania Magazine of History and Biography
Vol. 101, No. 4 (Oct., 1977), pp. 487-505 (19 pages)
https://www.jstor.org/stable/20091205  

List of 29 Companies in which scientific Management was introduced uring 1901 to 1916
Table 1 in JOURNAL ARTICLE
Scientific Management, Systematic Management, and Labor, 1880-1915
Daniel Nelson
The Business History Review
Vol. 48, No. 4 (Winter, 1974), pp. 479-500 (24 pages)
https://www.jstor.org/stable/3113537 

Frederick Taylor's Piece Rate System - 1895

  Part 1 -  Part 2   -  Part 3 -  Part 4 - Part 5 - Part 6

Engineering Elements Examined by Taylor apart from Task Elements.


Ud.  21.8.2022, 6.3.2022
Pub: 8.11.2021


Tuesday, August 30, 2022

Energy Efficiency Improvement of Machine Tools and Machine Shops - Energy Industrial Engineering

 Reducing energy costs in production with machine tools

Energy consumption is increasingly becoming the main concern for machine tool users. But energy costs are not the only factor here. Proof of climate-neutral production is increasingly becoming a competitive advantage in the production of parts with machine tools. 

SINUMERIK equipment packages as well as CNC Shopfloor Management Software from Siemens make a significant contribution to increasing the energy efficiency of the machine.



Energy-efficient machining systems: A critical review
June 2014The International Journal of Advanced Manufacturing Technology 72(9-12):1389-1406
DOI:10.1007/s00170-014-5756-0
Project: Development of an energy-efficient machining system
https://www.researchgate.net/publication/272031225_Energy-efficient_machining_systems_A_critical_review


Energy efficiency of machining operations: A review
January 2016Proceedings of the Institution of Mechanical Engineers Part B Journal of Engineering Manufacture 231(11)
DOI:10.1177/0954405415619345
https://www.researchgate.net/publication/292213278_Energy_efficiency_of_machining_operations_A_review

Earlier Collection



1. C.-W. Park, K.-S. Kwon, W.-B. Kim, B.-K. Min, S.-J. Park, I.-H. Sung, Y. S. Yoon, K.-S. Lee, J.-H. Lee, J. Seok, "Energy consumption reduction technology in manufacturing—A selective review of policies standards and research", Int. J. Precis. Eng. Manuf., vol. 10, pp. 151-173, Dec. 2009.   
 

2. F. Liu, J. Xie, S. Liu, "A method for predicting the energy consumption of the main driving system of a machine tool in a machining process", J. Cleaner Prod., vol. 105, pp. 171-177, Oct. 2015.

Liu et al.  divided energy consumption into three stages, start-up, idle, and cutting, and developed a predictive model considering the characteristics of cutting force, rotation speed, kinetic energy, and magnetic field energy for each stage.
   
3. S. H. Hu, "Energy consumption characteristics of multiple-component of modern CNC machine tools", vol. 3, 2012.
 
4. S. Anderberg, S. Kara, "Energy and cost efficiency in CNC machining", Proc. 7th CIRP Conf. Sustain. Manuf., pp. 1-4, 2009.

In the extreme case with the highest forecasted energy cost and full automation, the energy cost account for as much as 14% of the total machining cost. But typical rate is less than 2% of the total machining cost.

 
5. DMG MORI Going Green With New Energy-Saving Functions, Sep. 2014, [online] Available: https://www.dmgmori.co.jp/corporate/en/news/pdf/20140905_energy_e.pdf.
 
6. Energy-Efficient Machine Tool Technologies for Any Size Shop, 2016, [online] Available: https://www.okuma.com/stuff/contentmgr/files/0/143c354d61f2562efb3e2a8bd72166a0/files/okuma_energyefficientmachinetooltechnologies_whitepaper_final_high_ res.pdf.
 
7. Utilization Monitoring and Analysis, [online] Available: https://english.mazak.jp/smooth-technology/monit_analysis/.

 In response to these needs for energy reduction and management, leading makers of machine tools (e.g., DMG MORI, Okuma, and Mazak) are developing and commercializing human-machine interface (HMI) systems with energy monitoring functions, which support the energy consumption monitoring of representative machine tool components, such as spindles and servo motors. The purpose of this type of energy monitoring is to achieve the efficient consumption and management of energy while supporting more accurate control and decision-making.
 
8. G. May, B. Stahl, M. Taisch, D. Kiritsis, "Energy management in manufacturing: From literature review to a conceptual framework", J. Cleaner Prod., vol. 167, pp. 1464-1489, Nov. 2017.

Vikhorev et al.  proposed a framework for monitoring and managing the energy consumption of factories. The framework collects energy data from energy-consuming objects in factories such as machine tools, generates events, avoids peak loads through an event-streaming engine called complex event processing (CEP), and assists decision-making by calculating energy consumption-related key performance indicators (KPIs).
   
   
9. V. A. Balogun, P. T. Mativenga, "Modelling of direct energy requirements in mechanical machining processes", J. Cleaner Prod., vol. 41, pp. 179-186, Feb. 2013.

Balogun and Mativenga  developed a machine tool energy consumption model for the electrical energy requirements of machining toolpaths. This model considers the idle state as well as the cutting state and further refines the power characteristics of coolant and tool changes
   
10. T. Peng, X. Xu, L. Wang, "A novel energy demand modelling approach for CNC machining based on function blocks", J. Manuf. Syst., vol. 33, no. 1, pp. 196-208, Jan. 2014.

 Peng et al. [13] developed an approach to modeling the energy demands of computer numerical control (CNC) machines through function block (FB) modeling based on the International Electrotechnical Commission (IEC) international standard IEC 61499. The FB specifies the in/out data and processing process by subdividing the hardware components. The approach is implemented to support the monitoring of energy consumption by subdividing down to fundamental levels, such as spindles and feed axes.
   
11. N. Xie, M. Duan, R. B. Chinnam, A. Li, W. Xue, "An energy modeling and evaluation approach for machine tools using generalized stochastic Petri nets", J. Cleaner Prod., vol. 113, pp. 523-531, Feb. 2016.

Xie et al. proposed an energy consumption model based on stochastic Petri nets. Through the proposed model, an environment for evaluating productivity-related indicators such as cycle time in connection with energy consumption was established. In addition, research has been conducted on developing a framework for more efficient energy data monitoring.
   
12. X. Chen, C. Li, Y. Tang, Q. Xiao, "An Internet of Things based energy efficiency monitoring and management system for machining workshop", J. Cleaner Prod., vol. 199, pp. 957-968, Oct. 2018.

Chen et al.  developed a system for processing and monitoring energy data collected from various sensors and machine controllers via the internet of things (IoT). In addition, there are several researches about energy consumption efficiency.

   
13. T. Schudeleit, S. Züst, L. Weiss, K. Wegener, "The total energy efficiency index for machine tools", Energy, vol. 102, pp. 682-693, May 2016.

Schudeleit et al. proposed indexes for analyzing the energy efficiency of machine tools. They distinguished between indexes for sufficiency, efficiency, and consistency to quantify energy efficiency.
   
14. J. Lenz, J. Kotschenreuther, E. Westkaemper, "Energy efficiency in machine tool operation by online energy monitoring capturing and analysis", Procedia CIRP, vol. 61, pp. 365-369, 2017.

 Lenz et al.  developed similar energy efficiency measures and implemented an online-based monitoring system for capturing energy efficiency.
   
15. K. Schischke, E. Hohwieler, R. Feitscher, J. König, S. Kreuschner, P. Wilpert, N. F. Nissen, "Energy-using product group analysis-lot 5 machine tools and related machinery executive summary-final version", Aug. 2012.

 The Fraunhofer institute  defined and classified components for monitoring of a machine tool’s energy consumption and the details are available in the paper.
 
16. Q. Xiao, C. Li, Y. Tang, Y. Du, Y. Kou, "Deep learning based modeling for cutting energy consumed in CNC turning process", Proc. IEEE Int. Conf. Syst. Man Cybern. (SMC), pp. 1398-1403, Oct. 2018.   Full Text: PDF (362KB)

Xiao et al.  applied deep learning models, such as convolutional neural networks (CNNs), sparse auto encoders (SAEs), and deep belief networks (DBNs), and compared the results to predict energy consumption during processing. The power of the processing stage was subdivided into standby power, unload power, material removal power, additional load loss, and cutting-related auxiliary system power, and an SAE was found to be the most efficient method.

170. G. Y. Zhao, Z. Y. Liu, Y. He, H. J. Cao, Y. B. Guo, "Energy consumption in machining: Classification prediction and reduction strategy", Energy, vol. 133, pp. 142-157, Aug. 2017.

 Zhao et al. [20] studied energy modeling and prediction methodologies from various perspectives, such as tool wear, tool intrinsic energy, and artificial neural networks.
   
18. P. Liu, F. Liu, H. Qiu, "A novel approach for acquiring the real-time energy efficiency of machine tools", Energy, vol. 121, pp. 524-532, Feb. 2017.

Liu et al.  developed a methodology for obtaining the real-time energy efficiency (REE) of machine tools. A model was developed to derive REE from the input power of the spindle as well as actual consumption data and related processing variables without measuring the cutting force of the machine, thereby laying the foundation for more efficient energy consumption.
   
192. T. Peng, X. Xu, "An interoperable energy consumption analysis system for CNC machining", J. Cleaner Prod., vol. 140, pp. 1828-1841, Jan. 2017.

Peng and Xu  developed a process that can perform hybrid modeling considering both the 3-axis and the 5-axis for an interoperability-based energy consumption analysis. In addition, an interoperable data model has been developed for monitoring and optimization of energy consumption based on the STEP-NC standard for exchange of product data.
   
20. X. Zhou, F. Liu, W. Cai, "An energy-consumption model for establishing energy-consumption allowance of a workpiece in a machining system", J. Cleaner Prod., vol. 135, pp. 1580-1590, Nov. 2016.

 Zhou et al.  developed a model to establish energy consumption allowance in a machining system. They defined the energy consumption step of the machining system and the input power profile and model of each step in detail. In addition, various studies have been conducted regarding the milling process and energy consumption
   
21. C. Zhang, Z. Zhou, G. Tian, Y. Xie, W. Lin, Z. Huang, "Energy consumption modeling and prediction of the milling process: A multistage perspective", Proc. Inst. Mech. Eng. B J. Eng. Manuf., vol. 232, no. 11, pp. 1973-1985, Sep. 2018.

Zhang et al. developed energy consumption modeling and a prediction model of milling processes. They used multiple linear regressions, a sliding filter, and variable neighborhood search–based gene expression programming to model energy consumption.
   
22. Z. Shang, D. Gao, Z. Jiang, Y. Lu, "Towards less energy intensive heavy-duty machine tools: Power consumption characteristics and energy-saving strategies", Energy, vol. 178, pp. 263-276, Jul. 2019.

Shang et al.  strategy includes relations of power consumption between cutting and air-cutting states and assists in designing and using energy within machining process.
   
23. X. Luan, S. Zhang, J. Chen, G. Li, "Energy modelling and energy saving strategy analysis of a machine tool during non-cutting status", Int. J. Prod. Res., vol. 57, no. 14, pp. 4451-4467, Jul. 2019.

Luan et al.  proposed an energy modeling and saving strategy analysis of machine tools during the non-cutting status. They developed models of energy consumption in the idle status of machine tools.
   
24. C. Li, L. Li, Y. Tang, Y. Zhu, L. Li, "A comprehensive approach to parameters optimization of energy-aware CNC milling", J. Intell. Manuf., vol. 30, no. 1, pp. 123-138, Jan. 2019.

Li et al.  proposed a comprehensive approach to the parameter optimization of energy-aware CNC milling. They developed an energy consumption model for the main status and elements of machine tools using a non-linear regression. In addition, an optimization model of energy consumption was developed using the tabu search method.
   
25. A. Aramcharoen, P. T. Mativenga, "Critical factors in energy demand modelling for CNC milling and impact of toolpath strategy", J. Cleaner Prod., vol. 78, pp. 63-74, Sep. 2014.
   
26. Optimizing Material Removal Rates, [online] Available: https://www.harveyperformance.com/in-the-loupe/material-removal-rate-efficiency/.
 

27 TS B, 0024-1:2010, "Machine Tools-Test Methods for Electric Power Consumption—Part 1: Machining Centres", 2010.
 
28. Y. C. Liang, X. Lu, W. D. Li, S. Wang, "Cyber physical system and big data enabled energy efficient machining optimisation", J. Cleaner Prod., vol. 187, pp. 46-62, Jun. 2018.
   

29. S. Tian, T. Wang, L. Zhang, X. Wu, "An energy-efficient scheduling approach for flexible job shop problem in an Internet of manufacturing Things environment", IEEE Access, vol. 7, pp. 62695-62704, 2019.  Full Text: PDF (15919KB)  

Above 29 references are from:
H. S. Kang, J. Y. Lee and D. Y. Lee, "An Integrated Energy Data Analytics Approach for Machine Tools," in IEEE Access, vol. 8, pp. 56124-56140, 2020.
https://ieeexplore.ieee.org/document/9040402


30. Improving Energy Efficiency in CNC Machining - PhD Thesis
by SS Pavanaskar · 2014
87 pages - PDF

 In this century, we must put forth the objective of energy efficiency as well as productivity when researching new and existing manufacturing processes. In this dissertation, we study CNC milling with this combined objective.
















Industrial Engineering For Efficient Energy Use


Energy Efficiency in Data Centers - Federal Energy Management Program
The Federal Energy Management Program (FEMP) encourages agencies and organizations to improve data center energy efficiency in accordance with the Office of Management and Budget's Smart Cloud Strategy and M-16-19 Memorandum.

Data centers offer a tremendous opportunity for energy and cost savings.

How data centers can minimize their energy use
ABB Review | 03/2020 


25.1.2014
Failing to accurately account for the cost of energy in manufacturing can be a recipe for failure.
http://www.automationworld.com/energy-use-critical-ingredient-manufacturing-success#!

3.11. 2013
Energy Efficiency - ABB


7.7.2011
The Knol is being updated after one and half years. The motivation for the update is an article published in the Industrial Engineering Magazine (IIE Magazine) July 2011 with the title Energizing Continuous Improvement by John Preston,
John Preston is a corporate industrial engineer and president of IIE’s Greater Detroit Chapter. He is employed by Dura Automotive Systems in Rochester Hills, Mich.
He gave ideas on improving energy efficiency. I am summarizing the article in another knol.


20 December 2009

 

Industrial Engineering and Energy

Industrial engineering profession decided to evaluate and improve the efficiency of energy use and hence included energy in its definition. It also added information to its definition with the same objective.
But has industrial engineering developed any methodologies for evaluating and improving energy use efficiency? This knol is an attempt to collect material relating to efficient energy use.
___________________________________________________________________________________________

Industrial Engineering in the field of Energy and Environmental Engineering

Münster/Steinfurt (23 February 2007)

Sales, management or controlling - only a few other degree programmes give graduates access to such a wide range of professional opportunities as that in Industrial Engineering.

This is why Münster University of Applied Sciences has now added Industrial Engineering to its range of courses.

"By popular demand, we have decided to offer a degree programme in Industrial Engineering in the field of Energy and Environmental Engineering", Prof. Dr.-Ing. Christof Wetter, Dean of the Faculty of Energy · Building · Environment, underlined.
___________________________________________________________________________________________

ENERGY EFFICIENCY IN PRODUCTION ENGINEERING COURSES


Third International Conference on Production Research – Americas’ Region 2006 (ICPR ICPR-AM06)
___________________________________________________________________________________________

Data center energy efficiency assessment by IBM services

IBM report: cutting energy costs for a powerful competitive advantage
IBM Data Center and Facilities Strategy Services – data center energy efficiency assessment measures the energy usage of your cooling, electrical and building systems, compares your energy efficiency to an industry standard and identifies opportunities to improve. It helps create business-case financial justification to help prioritize improvements for energy savings, giving you a framework to make infrastructure decisions.
___________________________________________________________________________________________

The Cisco Data Center Energy Efficiency Assessment Service

Increase the Energy Efficiency of Your Physical Design
The Cisco Data Center Energy Efficiency Assessment Service helps you to benchmark the power, cooling, and facilities infrastructure of your data center so you can increase its energy efficiency.
The service includes five activities:
● Inspect physical infrastructure
● Benchmark energy efficiency
● Project efficiency effects of changes
● Model air flow and temperature distribution
● Assess electrical efficiency
___________________________________________________________________________________________
7.7.2011
The Knol is being updated after one and half years. The motivation for the update is an article published in the Industrial Engineering Magazine (IIE Magazine) July 2011 with the title Energizing Continuous Improvement by John Preston,
John Preston is a corporate industrial engineer and president of IIE’s Greater Detroit Chapter. He is employed by Dura Automotive Systems in Rochester Hills, Mich.
He gave ideas on improving energy efficiency. I am summarizing the article in another knol.
Original knol - http://knol.google.com/k/narayana-rao/industrial-engineering-for-efficient/2utb2lsm2k7a/ 2061



Ud. 30.1.2022,  25.1.2014, 7.7.2011

Progress of Scientific Management - Productivity Improvement - Subsequent to F.W. Taylor

Is Scientific Management progressing today.

The notion that science of management can be developed and used in very much in use today.

But the focus of scientific management, as captured by Taylor was work of individuals. That focus is not any more popular. The discussion regarding individual work is researched by HRM, Ergonomics and OB disciplines. Even in IE field, attention to individual's work has come down

Henry Lawrence Gantt

Henry Lawrence Gantt was a teacher of natural science and mechanics, and later a mechanical engineer. In 1887 he joined the Midvale Steel Co. as an assistant in the engineering department. He met Frederick Taylor there, and they shared a common interest in their quest for science in management and developed a deep mutual admiration for each other's work. In Gantt's teaching the worker, Gantt felt the supervisor should do more than to increase the worker's skill and knowledge; he added another ingredient to industrial education called the "habits of industry". These habits were industriousness and cooperation, which would facilitate the acquisition of all other knowledge. The habits that had to be taught to the worker were those of, "doing promptly and to the best of his ability the work set before him". Gantt was oriented toward the dramatization of data through graphic means. It thus allowed management to see how plans were progressing and take whatever action was necessary to keep projects on time or within budget authorizations. Gantt never patented the concept, nor profited from it, but his achievement did earn him the Distinguished Service Medal from the Government. 

Gantt is often seen as a disciple of Taylor and a promoter of the scientific school of management. In his early career, the influence of Taylor - and Gantt's aptitude for problem-solving - resulted in attempts to address the technical problems of scientific management. Like Taylor, Gantt believed that it was only the application of scientific analysis to every aspect of work which could produce industrial efficiency, and that improvements in management came from eliminating chance and accidents. Gantt made four individual and notable contributions. 

Henry Laurence Gantt's legacy to management is the Gantt chart. Accepted as a commonplace project management tool today, it was an innovation of world-wide importance in the 1920s. But the Chart was not Gantt's only legacy; he was also a forerunner of the Human Relations School of management and an early spokesman for the social responsibility of business (Management & Business Studies Portal of British Library). 

Henry Laurence Gantt (1861-1919) - Industrial Engineer

https://en.wikipedia.org/wiki/Henry_Gantt

Carl G. Barth, a mathematics teacher, was recruited by Taylor for the purposes of handling the complex mathematical problems in Taylor's metal cutting experiments. When Taylor left Bethlehem, Carl Barth went with him and then assisted in the first installations of scientific management at the Tabor Manufacturing Co., The Link Belt Co., Fairbanks Scale, Yale and Towne, and at a later time, Watertown Arsenal. Mr. Barth also assisted George Babcock in installing scientific management in the Franklin Motor Car Co. His slide rule was unique and helpful.  In 1905 Barth began work as an independent consultant. For two decades he traveled to various plants, including the United States Arsenal at Watertown, Massachusetts (1909), installing his slide rule systems. Though officially retired in 1923, Barth continued to make slide rules. In addition to feed-and-speed slide rules, Barth created slide rules for calculations related to gears, belts, helical springs, and more (Collections of Historical Scientific Instruments / Harvard University).  

In 1904, Mr. Harrington Emerson installed better methods and equipment, centralized the manufacture of material and tools, and installing an individual reward system in Santa Fe Railway. Mr. Emerson's methods were praised as an example of what scientific management could do for the railroads. Waste and inefficiency were the evils that Mr. Emerson saw pervading the entire U.S. industrial system. Mr. Emerson made other contributions in cost accounting. In using Hollerith punch-card tabulating machines for accounting records, and in setting standards for judging worker and shop efficiency. 

 Emerson efficiency methods were applied to department stores, hospitals, colleges, and municipal governments. Between 1911 and 1920 Emerson's firm averaged annual earnings of over $100,000.00.  Emerson occupied himself with soliciting business and managing the financial affairs of the company, leaving the consulting work to his associates. Branch offices were established in New York, Pittsburgh, and Chicago. In addition to business success. Emerson enjoyed growing stature in the engineering profession. He was identified as one of the pioneers of modern management and industrial engineering, along with Taylor, H. L. Gantt, and Frank Gilbreth. Emerson joined these and other progressive engineers in founding the Society of Industrial Engineers in 1917.  Emerson also participated in the engineering profession's defense of scientific management against public misconception and antagonism from labor organizations. He testified in 1912 before a U.S. House of Representatives committee investigating the impact of scientific management on labor. He also submitted a statement in 1914 to the United States Commission on Industrial Relations, later undergoing cross-examination as well (Harrington Emerson Papers, Emerson, Harrington, 1853 -1931).

Morris Llewellyn Cooke went to work in industry after having received a B.S. Degree in mechanical engineering and was soon applying a "question method" to the wastes of industry long before he met, or heard of, F.W. Taylor. To scientific management, Morris Cooke had brought new ideas to develop harmonious cooperation between labor and management. He wanted more participation by workers, but most of all he sought to enlist aid of the leaders of organized labor. If scientific management was to make any headway in the Twentieth century, it required someone like Mr. Cooke to open new vistas in nonindustrial organizations and gain the support of the U.S. labor movement. 

During Roosevelt's first term as Governor of New York, he appointed Cooke to the Power Authority of the State of New York. Later, in March 1935, Roosevelt selected Cooke to head the Rural Electrification Administration which he funded through the Emergency Relief Appropriation Act of that year.  

 Harlow S. Person introduced the first opportunity for college training of employment managers at Dartmouth's Amos Tuck School of Administration and Finance as early as 1915. Those at Tuck whom wished to become employment managers had the opportunity to take a "special course in employment management and (prepare) a thesis which is the solution of a specific problem of management in a specific plant". Through his role in the Society for the Promotion of the Science of Management (SPSM), later was renamed the Taylor Society, Person was able to promote the study of employment management from a systematic point of view.  Under Harlow Person's presidency, the Taylor Society from 1914 through 1919 was increasingly receptive to the consideration of social ideals and to the participation of social scientists and reformers. Harlow Person, and Henry Dennison, Van Kleeck in the 1920s helped to make the Taylor Society an imaginative forum for the discussion of scientific management's relation to problems of macroeconomic coordination (Person, "The Manager, the Workman, and the Social Scientist"; Haber, Efficiency and Uplift, chap. 3; Nelson, Frederick W. Taylor, chap. 7; Noble, America By Design, chap. 10; Schachter, Taylor and the Public Administration Community, chap).  

 Hugo Munsterberg was the creator of industrial psychology. In 1892, Munsterberg established his psychological laboratory at Howard University. It was to become the foundation stone in the industrial psychology movement. Munsterberg's Psychology and Industrial Efficiency was directly related to Taylor's proposals and contained three broad parts, 1.) "The Best Possible Man", 2.) "The Best Possible Work” and 3 "The Best Possible Effect". Munsterberg's focus on the individual, the emphasis on efficiency, and the social benefits to be derived from application of the scientific method, had been what F.W. Taylor and others had envisioned as contributions from Psychologists to research into the human factor. 

 His paper Psychology and the Market (1909) suggested that psychology could be used in many different industrial applications including management, vocational decisions, advertising, and job performance and employee motivation. In Psychology and Industrial Efficiency (1913) Münsterberg addressed many different topics.  His objective was "to sketch the outlines of a new science which is to intermediate between the modern laboratory psychology and the problems of economics: the psychological experiment is systematically to be placed at the service of commerce and industry." (Münsterberg, Hugo. Psychology and Industrial Efficiency. Boston and New York: Houghton Mifflin Company, 1913. Print (3). He selects three points of view that he believes are of particular importance to industrial psychology and seeks to answer those questions. These three questions include "how we can find the men whose mental qualities make them best fitted for the work which they have to do; secondly, under what psychological conditions we can secure the greatest and most satisfactory output of work from every man; and finally, how we can produce most completely the influences on human minds which are desired in the interest of business." In other words, we ask how to find "the best possible man, how to produce the best possible work, and how to secure the best possible effects." (Münsterberg, Hugo. Psychology and Industrial Efficiency. Boston and New York: Houghton Mifflin Company, 1913. Print (23-24). 

Whiting Williams, vice president and director of personnel for the Hydraulic Pressed Steel Co. located in Cleveland,  shed his white collar and headed out disguised as a worker to study industrial conditions first￾hand. He felt that the only way to discover the human problems of industry would be to become a participant-observer because "men's actions spring from their feelings rather than their thoughts, and people cannot be interviewed for their feelings". Mr. Williams' view was unique in that he established earnings as a means of social comparison - that is, the pay a worker received was considered not in absolute, but in relative, terms to what others received.  In addition, he was active as a writer and speaker on the subject of employee-management relations across the country (Oberlin College Archives). 

Robert. G. Valentine was one early revisionist who attempted a rapprochement between unions and scientific management as represented by the Taylor Society. He argued that the labor-management relationship was properly one of "consent". Consent was based on workers participation, and especially union participation, in reaching all decisions affecting labor.  

Russell Robb, gave series of lectures on organization at the newly formed Harvard Business School,  Mr. Robb was heavily influenced by scientific management and the need for systematization, but he looked beyond that to see the organization as a whole. 

References 

http://en.wikipedia.org/wiki/Frederick_Winslow_Taylor

http://dssmhi1.fas.harvard.edu/emuseumdev/code/emuseum.asp?action=advsearch&newsearch=

1&profile=people&rawsearch=constituentid/,/is/,/964/,/false/,/true&style=single&searchdesc=Ca

rl%20G.%20Barth

http://www.mbsportal.bl.uk/taster/subjareas/busmanhist/mgmtthinkers/gantt.aspx

http://www.libraries.psu.edu/findingaids/1541.htm

http://newdeal.feri.org/bios/bio10.htm

http://en.wikipedia.org/wiki/Hugo_M%C3%BCnsterberg

http://www.oberlin.edu/archive/holdings/finding/RG3/SG2/biography.html


Source of the paper

https://www.academia.edu/9120152/The_Advent_of_Scientific_Management



Implementation of Scientific Management by Taylor's Followers

FIRM    PRINCIPAL  TAYLOR EXPERT( S) DATES 


1 Tabor Mfg., Phila.   Barth, Hathaway 1903-

2 Stokes and Smith, Phila.  Gantt 1902-03? 

3 Link Belt Engr., Phila. Barth 1903-07 

4 Sayles Bleachery, Saylesville, R.I. Gantt 1904-08 

5 Yale & Towne, Stamford, Conn. Barth 1905-07 

6 Santa Fe Railroad, Topeka, Kan. Emerson 1904-07 

7 Brighton Mills, Passaic, N.J. Gantt 1905-08 

8 Ferracute Machine, Bridgeton, N.J. Parkhurst 1907-10 

9 H. H. Franklin, Syracuse, N.Y. Barth 1909-10, 1911 

10 Canadian Pacific Railroad, Montreal  Gantt 1908-11 

11 Smith & Furbush Machine, Phila. Barth 1908-10



The key features of Taylor's system. 

( 1) the preliminary technical and organizational improvements, such as changes in machinery and machine operations ( including the introduction of high speed tool steel in machine shops), better belting, cost accounting procedures,  systematic purchasing, stores and tool room methods - in short, Taylor's basic refinements of systematic management techniques; ( 2) a planning department; ( 3) functional foremanship; ( 4) time study; and ( 5) an incentive wage system. Study by Nelson indicates that  Taylor's colleagues were generally faithful to his teachings. They typically introduced major changes in three or four of the categories. The principal exceptions were functional foremanship, which most of them apparently considered impractical, and to a lesser extent, the incentive wage, which they advocated but often did not have an opportunity to introduce. The usual effect of their work, then, was a wide-ranging revision of the physical organization of the plant, a less thorough alteration of the foreman's functions, and a modest change in the average workman's activities. 

In every company there was evidence of preliminary reorganization: materials were classified and standardized, tool and store rooms revamped, machinery adjusted, and the plant layout improved. The only major exception to Taylor's approach was in accounting procedure, where the "experts" often made only minor changes.


Monday, August 29, 2022

Computer Aided Production Engineering

 CAPE is seen as a new type of computer-aided engineering environment which will improve the productivity of manufacturing/industrial engineers. This environment would be used by engineers to design and implement future manufacturing systems and subsystems. Work is currently underway at the United States National Institute of Standards and Technology (NIST) on CAPE systems. The NIST project is aimed at advancing the development of software environments and tools for the design and engineering of manufacturing systems.

https://en.wikipedia.org/wiki/Computer-aided_production_engineering




Computer Aided Production Engineering: CAPE 2003

J. A. McGeough (Editor)


ISBN: 978-1-860-58404-6 May 2003 480 Pages

https://www.wiley.com/en-us/Computer+Aided+Production+Engineering%3A+CAPE+2003-p-9781860584046


https://www.nist.gov/publications/computer-aided-manufacturing-engineering


https://www.nist.gov/nist-pub-series/nist-interagencyinternal-report-nistir


Computer-Aided Manufacturing System Engineering

PublishedJune 1, 1993

Author(s)

Charles R. McLean

Abstract

A new type of computer-aided engineering environment is envisioned which will improve the productivity of manufacturing/industrial engineers. This environment would be used by engineers to design and implement future manufacturing systems and subsystems. the work which is currently underway at the United States National Institute of Standards and Technology (NIST) on computer-aided manufacturing system engineering environments is described. The NIST project aims to advance the development of software environments and tools for the design and engineering of manufacturing systems. The paper presents an overall vision of the proposed environment, identifies technical issues which must be addressed, and describes work on a current prototype computer-aided manufacturing system engineering environment.

Proceedings TitleProceedings of the IFIP TC5/WG5.7 International Conference on Advances in Production Management Systems APMS '93

https://www.nist.gov/publications/computer-aided-manufacturing-system-engineering


Sunday, August 28, 2022

100 New Technologies in Industry 4.0 Era - How Many Do You Know?

Source: Article

Industry 4.0 and World Class Manufacturing

Integration: 100 Technologies for a WCM-I4.0 Matrix

Lorenzo D’Orazio, Roberto Messina and Massimiliano M. Schiraldi *

Department of Enterprise Engineering, Tor Vergata University of Rome, Via del Politecnico, 00133 Rome, Italy;

 MDPI 

Applied Sciences

Appl. Sci. 2020, 10, 4942; doi:10.3390/app10144942

100 Technologies for a World Class Manufacturing - Industry 4.0 Matrix

1 Automatic Real-Time Cloud-based Data Acquisition (Energy Consumption, Efficiency, Wear, Heat, Pollution, Noise, Workload, Product Data, Production Data, Competence)

2 S-EWO/EWO/HERCA recording with workplace device 

3 Tag recording with workplace device

4 Real-Time Cloud-based automatic analytics 

5 Cloud Database with WCM tools accessible with workplace device 

6 Real-Time parameters monitoring with glass visualization 

7 Recording of Bordereau and Scraps with workplace device 

8 Alert systems for nonuse 

9 Alarm systems for training needed 

10 Automatic machine stop due to unsafe conditions 

11 PPE check use with Camera 

12 Automatic machine stop due to starving situation 

13 Glass visualization of AM/CIRL/PM Calendar 

14 Automatic Warning due to the missing of basic conditions 

15 Assisted Control of Basic conditions with workplace device 

16 Guided CIRL/AM(SMP)/PM/Operative Procedure (SOP/OPL) activities step by step

17 Glass visualization of dirt source 

18 CIRL/AM/PM calendar visualization with workplace device 

19 Dirt source monitoring 

20 Lubrification Points Monitoring 

21 Automatic warning on people on range due to machine anomalies Project building

22 WhatsApp messages of malfunctioning 

23 Glass visualization of malfunctioning parts 

24 Automatic Warning on next and previous machines of malfunctioning parts 

25 Notice of planned CIRL/AM/PM activities 



26 RFID objects identification and localization 

27 RFID tags which store instructions for cleaning tools and objects 

28 Glass visualization of where replace instruments 

29 Substitution of physical shadow board with virtual board 

30 Robot Collaborative/Exoskeletons support 

31 AGV systems for bins and container transportation/picking activities 

32 RFID tag with procedure instructions 

33 Autonomous workload deployment among the machines 

34 RFID tag embedded in unfinished products to prepare next machine production

35 Workload shift among stations given by real-time production data analysis 

36 Automatic Machine configuration 

37 IT Systems directly connected with MES and PLC 

38 Glass visualization of unloading procedure goods for suppliers 

39 Automatic request on workplace device of switching workstation 

40 Operation tuning and better performance with 3D Printing Technology 

41 Digital Platform—opportunity to allocate orders watching at suppliers’ capacity

42 AGV guided by machines needs indication 

43 RFID tag on unfinished products to track them in real time 

44 Continuous stock monitoring with RFID tag 

45 Virtual CAD model on Kanban loops 

46 Real-Time Kanban optimal size and frequency Simulation  

47 Autonomous Kanban system among stations 

48 Vocal/Maps interactive guide to find the SKU 

49 Real-Time Simulation of picking activities path to have the faster one 

50 Glass visualization of stock data 


51 Forklift embedded of sensor mapping the human in the area

52 Automatic braking of forklift sensing a human in a close distance

 53 Pedestrian equipped with map of forklift in movement

54 Cloud-based shipping slot booking

55 Glass visualization of current component health status

56 HMI panel with procedure to solve anomalies by operator

57 Automatic call of the machine to maintainer

58 Machine learning abilities to learn how to solve new anomalies

59 Machine Learning to prevent unsafe conditions

60 Automatic warning with workplace device of abnormal condition of the component

61 Machine learning Quality control for nonlinear defect’s pattern

62 Real-Time Cloud-based automatic analysis of component remaining life

63 Glass visualization of component remaining life

64 Vertical integration in a shared Digital online CAD Platform

65 Digital Twin plant simulation

66 Horizontal integration in a shared technical database

67 Plug and Play system to create a modular design of the machine

68 Simulation of workplace environment for risk assessment

69 Intelligent Cloud-based Checklist

70 Deep and Reinforcement Learning to predict component remaining life

71 Cloud Database with production engineer’s workload linked with Team

72 Alarm System for excessive workload

73 Automatic optimization of workload in a new scenario

74 Reminder system for ongoing project

75 Glass visualization for how to solve anomalies



76 Glass visualization of CIRL/AM/PM/SOP/OPL/SMP SMED procedure

77 Virtual Training Simulation (Machine Breakdown, WCM tools, SMED,

78 Efficiency Data on HMI and Workplace device

79 Tool/utilization glass—guided

80 Tips directly sent to Responsible

81 Tips status directly visible by operator with workplace device

82 Automatic Lighting of part to be handled/picked

83 Common shared Platform with other company’s plant

84 Automatic Scraps Categorization given by machine sensors

85 Automatic Warning of out of parameters process

86 Common shared Platform with Customer and Suppliers

87 Claim directly sent to Line Leader and Quality Manager

88 Glass Visualization of Product Defect

89 Line Process Simulation

90 Visual Camera Poka-Yoke and Product’s parameters monitoring

91 Virtual Test to assess competence with automatic gap definition and training needed

92 Machine Learning to prevent reworking and to set correct machine parameters

93 Online Test to assess competence with automatic gap definition and training needed

94 RFID Tag for each employer’s badge with his information

95 Automatic data analysis on absenteeism for machine and department

96 Automatic data analysis on absenteeism cause

97 Glass visualization of defects linear and nonlinear

98 Production pace tuning according to buffer levels

99 Simulation of workplace environment for ergonomic optimization

100 Glass visualization of heavy packs 


Industry 4.0 - IIoT - Productivity Engineering

Industry 4.0 - IIoT - Productivity Management Implications and Applications.


More Details on 100 Technologies



1 Automatic Real-Time Cloud-based Data Acquisition (Energy Consumption, Efficiency, Wear, Heat, Pollution, Noise, Workload, Product Data, Production Data, Competence)

2 S-EWO/EWO/HERCA recording with workplace device 

   HERCA (Human Error Root Cause Analysis)

3 Tag recording with workplace device

In occupational health and safety, a tagging system is a system of recording and displaying the status of a machine or equipment, enabling staff to view whether it is in working order. It is a product of industry-specific legislation which sets safety standards for a particular piece of equipment, involving inspection, record-keeping, and repair. This sets standardized umbrella terms for equipment and machinery (e.g. machinery, scaffolding, forklift, cherry picker) to be deemed 'safe to use'.

https://en.wikipedia.org/wiki/Tagging_system

4 Real-Time Cloud-based automatic analytics 

5 Cloud Database with WCM tools accessible with workplace device 

6 Real-Time parameters monitoring with glass visualization 

7 Recording of Bordereau and Scraps with workplace device 

8 Alert systems for nonuse 

9 Alarm systems for training needed 

10 Automatic machine stop due to unsafe conditions 

11 PPE check use with Camera 

12 Automatic machine stop due to starving situation 

13 Glass visualization of AM/CIRL/PM Calendar 

14 Automatic Warning due to the missing of basic conditions 

15 Assisted Control of Basic conditions with workplace device 

16 Guided CIRL/AM(SMP)/PM/Operative Procedure (SOP/OPL) activities step

by step

17 Glass visualization of dirt source 

Simulation of Rear Glass and Body Side Vehicle Soiling by Road Sprays

https://www.researchgate.net/publication/245535293_Simulation_of_Rear_Glass_and_Body_Side_Vehicle_Soiling_by_Road_Sprays

18 CIRL/AM/PM calendar visualization with workplace device 

19 Dirt source monitoring 

20 Lubrification Points Monitoring 

21 Automatic warning on people on range due to machine anomalies Project building

22 WhatsApp messages of malfunctioning 

23 Glass visualization of malfunctioning parts 

24 Automatic Warning on next and previous machines of malfunctioning parts 

25 Notice of planned CIRL/AM/PM activities 



26 RFID objects identification and localization 

27 RFID tags which store instructions for cleaning tools and objects Procedure)

28 Glass visualization of where replace instruments 

29 Substitution of physical shadow board with virtual board 

30 Robot Collaborative/Exoskeletons support 

31 AGV systems for bins and container transportation/picking activities 

32 RFID tag with procedure instructions 

33 Autonomous workload deployment among the machines 

34 RFID tag embedded in unfinished products to prepare next machine production

35 Workload shift among stations given by real-time production data analysis 

36 Automatic Machine configuration 

37 IT Systems directly connected with MES and PLC 

38 Glass visualization of unloading procedure goods for suppliers 

39 Automatic request on workplace device of switching workstation 

40 Operation tuning and better performance with 3D Printing Technology 

41 Digital Platform—opportunity to allocate orders watching at suppliers’ capacity

42 AGV guided by machines needs indication 

43 RFID tag on unfinished products to track them in real time 

44 Continuous stock monitoring with RFID tag 

45 Virtual CAD model on Kanban loops 

46 Real-Time Kanban optimal size and frequency Simulation  

47 Autonomous Kanban system among stations 

48 Vocal/Maps interactive guide to find the SKU 

49 Real-Time Simulation of picking activities path to have the faster one 

50 Glass visualization of stock data 


51 Forklift embedded of sensor mapping the human in the area

52 Automatic braking of forklift sensing a human in a close distance

 53 Pedestrian equipped with map of forklift in movement

54 Cloud-based shipping slot booking

55 Glass visualization of current component health status

56 HMI panel with procedure to solve anomalies by operator

57 Automatic call of the machine to maintainer

58 Machine learning abilities to learn how to solve new anomalies

59 Machine Learning to prevent unsafe conditions

60 Automatic warning with workplace device of abnormal condition of the component

61 Machine learning Quality control for nonlinear defect’s pattern

62 Real-Time Cloud-based automatic analysis of component remaining life

63 Glass visualization of component remaining life

64 Vertical integration in a shared Digital online CAD Platform

65 Digital Twin plant simulation

66 Horizontal integration in a shared technical database

67 Plug and Play system to create a modular design of the machine

68 Simulation of workplace environment for risk assessment

69 Intelligent Cloud-based Checklist

70 Deep and Reinforcement Learning to predict component remaining life

71 Cloud Database with production engineer’s workload linked with Team

72 Alarm System for excessive workload

73 Automatic optimization of workload in a new scenario

74 Reminder system for ongoing project

75 Glass visualization for how to solve anomalies



76 Glass visualization of CIRL/AM/PM/SOP/OPL/SMP SMED procedure

77 Virtual Training Simulation (Machine Breakdown, WCM tools, SMED,

VIRTUAL TRAINING AND SIMULATION DEVELOPMENT

Maximizing the effectiveness of training solutions and simulation-based learning to meet organizations' toughest educational needs

https://program-ace.com/expertise/virtual-training-simulation/

78 Efficiency Data on HMI and Workplace device

79 Tool/utilization glass—guided

80 Tips directly sent to Responsible

81 Tips status directly visible by operator with workplace device

82 Automatic Lighting of part to be handled/picked

83 Common shared Platform with other company’s plant

84 Automatic Scraps Categorization given by machine sensors

85 Automatic Warning of out of parameters process

86 Common shared Platform with Customer and Suppliers

87 Claim directly sent to Line Leader and Quality Manager

88 Glass Visualization of Product Defect

89 Line Process Simulation

90 Visual Camera Poka-Yoke and Product’s parameters monitoring

91 Virtual Test to assess competence with automatic gap definition and training

needed

92 Machine Learning to prevent reworking and to set correct machine parameters

93 Online Test to assess competence with automatic gap definition and training needed

94 RFID Tag for each employer’s badge with his information

95 Automatic data analysis on absenteeism for machine and department

96 Automatic data analysis on absenteeism cause

97 Glass visualization of defects linear and nonlinear

98 Production pace tuning according to buffer levels

99 Simulation of workplace environment for ergonomic optimization

100 Glass visualization of heavy packs 



Flow Manufacturing - 101 Mini-Case Studies - Schonberger - Book Information

Flow Manufacturing -- What Went Right, What Went Wrong: 101 Mini-Case Studies that Reveal Lean’s Successes and Failures


Richard J. Schonberger

CRC Press, 12-Nov-2018 - Business & Economics - 570 pages


This book tells 101 stories of company efforts to implement the many aspects of flow manufacturing -- including such topics as just-in-time production, total quality control, reorganization of factories into product-focused or customer-focused cells, plants-in-a-plant, material flows by the simplicity of visual kanban, supplier partnerships, quick setup of equipment, cross-training and job rotation of the work force, and many more. The 101 mini-case studies – dubbed "caselets" -- include 26 non-U.S. companies from 12 countries and cover a wide swath of industrial sectors, and include many well-known corporations such as Apple, Campbell Soup, Honeywell, and Boeing.

From the 1980s to the present, the author has been taking the message of process improvement and customer-focused excellence far and wide. In his brief factory tours, he compiled detailed notes and then organized them as brief reports — his analysis or take on what they do well and what needs improvement. In the main the reports were then sent back to the hosts of the plant tour. These factory tours and these follow-up reports form the basis of the large majority of this book’s caselets.

Many of the caselets bring to life process-improvement methodologies in detail. With lots of caselets to draw from, the readers will find vivid examples of similar companies and processes within their respective industries. For example, the caselets often include applications of advanced concepts in cost management, employee training, performance management, supply chains, and logistics as well as applications of plant layout, quick setup, material handling, quality assurance, scheduling, ergonomics, and flow analysis.

Preview: https://books.google.co.in/books?id=6zX3DwAAQBAJ

Saturday, August 27, 2022

Selection of Operators - Principle of Industrial Engineering



TAYLOR - NARAYANA RAO PRINCIPLES OF INDUSTRIAL ENGINEERING
https://www.proquest.com/docview/1951119980











Selection of Operators

_______________

There has to be science that guides selection of operators. Management has to select persons based on specified criteria for each category of jobs and then train them specially. Now it is being termed competence based approach. Taylor made it a principle in scientific management. Physical capacity, intelligence, aptitude,  knowledge, skill etc. are to be specified for each job category and appropriate way of testing people for these specifications are to be developed by management.

Principles of Industrial Engineering - Presentation 


by Dr. K.V.S.S. Narayana Rao in the 2017Annual Conference of IISE (Institute of Industrial and Systems Engineering) at Pittsburgh, USA on 23 May 2017

______________________________


______________________________


Principles of Industrial Engineering - Narayana Rao - Detailed List

Clicking on the link will take you to more detailed content on the principle


The full paper on the principles by Prof. K.V.S.S. Narayana Rao is now available for downloading from IISE 2017 Annual Conference Proceedings in Proquest Journal Base.


Selelction of Equipment is also an Important Principle of Industrial Engineering. The activity is part of Facilities Industrial Engineering (27.8.2022)

Updated on 27.8.2022, 1 August 2018, 6 July 2017

World Class Manufacturing - Schonberger - Excerpts

 

Page 3

If, for example, the latest cost report shows a negative cost variance in the welding, the onus is on the welding supervisor to cut costs. But how? The supervisor may crack the whip to get more output for the same labor cost. Alternatively, ask industrial engineering or quality engineering "to do a study."  

Principles of Motion Economy - Videos

INDUSTRIAL ENGINEERING is redesign (engineering) of Products, Facilities and Processes for Productivity increase.
Productivity Management Imperative for USA - McKinsey. Returning US productivity to its long-term trend of 2.2 percent annual growth would add $10 trillion in cumulative GDP over the next ten years (2023 - 2030).

INTRODUCTION TO MODERN INDUSTRIAL ENGINEERING. E-Book FREE Download. 


Human Effort Industrial Engineering is guided by Principles of Motion Economy. In each process, for each operation, human effort has to be recorded, in two handed process charts and still more micro charts as required for further productivity or industrial engineering analysis.
________________ ________________ ________________



Ud. 27.8.2022
Pub 4.2.2012

Lean is a Subset and Sub-brand of Industrial Engineering.

 

Lean is subset of IE with increased focus on flow and special focus on pull.

Lean is a sub-brand of industrial engineering. Like motion study, time study, method study, lean is also method or sub-brand of industrial engineering.



Lean focuses on temporary storage or delay step in process flow chart. To eliminate delays, lean modifies engineering in other steps. SMED is a modification of operation step. Pokayoke is a modification of Inspection step. Layout changes are modification of mechanical handling steps. Lean also modifies production planning procedures.

Read



Lean & IE


Lean Thinkers have to use Industrial Engineering Tools - especially process charts. [VSM] analysis is at a high level, without many details. To uncover every instance of every type of muda requires a detailed analysis using a portfolio of tools drawn from industrial engineering ... The most important of these are process mapping (to identify and categorize each step together with the time, distance and effort involved)... Womack and Jones, 1996.
Lean Management - Introduction - Evolution.


Combine Quality and IE in Lean Organizations - Womack and Jones - Lean Thinking (1996, 2003)


LEAN  MANAGEMENT

How to plan, organize, resource, direct and control lean systems?
Combine Quality and Productivity Functions.
The traditional quality function should be combined with a productivity (or "lean") function to create an "improvement function" able to eliminate muda of all sorts. - Womack and Jones.
Lean Management - Introduction - Evolution















Ud 27.8.2022
Pub 7.6.2021

Thursday, August 25, 2022

John Shook - Lean Manufacturing Consultant

John Shook mentioned as  Visiting Assistant Research Scientist in Industrial and Operations Engineering in University of Michigan.

Learning from Japan's Technology Management

Staff

Volume 2, Issue 1, Fall 1994

https://quod.lib.umich.edu/j/jii/4750978.0002.105/--learning-from-japans-technology-management?rgn=main;view=fulltext



Becoming Lean by John Shook - Presentation

https://www.slideshare.net/micrimson/becoming-lean-john-shook-lean-manufacturing


https://www.ame.org/hall-of-fame-inductee/john-shook







YouTube Videos on Lean Systems and Practices

365 Lessons and Case Studies Course on Industrial Engineering - Free Online Lessons - Access and Study.

https://nraoiekc.blogspot.com/2020/05/industrial-engineering-online-course.html




Lean Management - Introduction - Evolution


Lean Management for Enhancing Productivity - Prof. Narayana Rao
Presentation by Professor K.V.S.S. Narayana Rao, National Institute of Industrial Engineering, Mumbai, India on the occasion of Productivity Week Celebration of 2014 with the theme "Lean Management for Enhancing Productivity" for the Senior Managers of Tata Steel Limited, Jamshedpur.



How to Lead Lean Systems
John Shook - Former Toyota Manager
Uploaded 17 July 2012 by Industry Week
__________________

__________________

Value Stream Walk - Jim Womack
July 2012
__________________

__________________

Toyota Kata by Author Mike Rother
__________________

___________________



Ud. 25.8.2022
Pub. 29.8.2013

Lean Enterprise Institute - Associated Organizations

 

https://www.lean.org/

https://teachinglean.org/

https://leanglobal.org/


 Lean Enterprise Institute


Lean Enterprise Institute, Inc., was founded in 1997 by management expert James P. Womack, Ph.D., as a nonprofit research, education, publishing, and conference company with a mission to advance lean thinking around the world. We teach courses, hold management seminars, write and publish books and workbooks, and organize public and private conferences. We use the surplus revenues from these activities to conduct research projects and support other lean initiatives such as the Lean Education Academic Network and the Lean Global Network. Visit LEI at https://www.lean.org for more information.


https://www.lean.org/about-lei/press-releases/page/13/

Definition of Management - F.W. Taylor



Management is  knowing exactly what you want men to do, and then seeing that they do it in the best and cheapest way. - F.W. Taylor.



The art of management has been defined, "as knowing exactly what you want men to do, and then seeing that they do it in the best and cheapest way.'" No concise definition can fully describe an art, but the relations between employers and men form without question the most important part of this art. In considering the subject, therefore, until this part of the problem has been fully discussed, the other phases of the art may be left in the background.



It is safe to say that no system or scheme of management should be considered which does not in the long run give satisfaction to both employer and employee, which does not make it apparent that their best interests are mutual, and which does not bring about such thorough and hearty cooperation that they can pull together instead of apart.

What the workmen want from their employers beyond anything else is high wages, and what employers want from their workmen most of all is a low labor cost of manufacture.

These two conditions are not diametrically opposed to one another as would appear at first glance. On the contrary, they can be made to go together in all classes of work, without exception, and in the writer's judgment the existence or absence of these two elements forms the best index to either good or bad management.

This book is written mainly with the object of advocating high wages and low labor cost as the foundation of the best management, of pointing out the general principles which render it possible to maintain these conditions even under the most trying circumstances, and of indicating the various steps which the writer thinks should be taken in changing from a poor system to a better type of management.

The condition of high wages and low labor cost is far from being accepted either by the average manager or the average workman as a practical working basis. It is safe to say that the majority of employers have a feeling of satisfaction when their workmen are receiving lower wages than those of their competitors. On the other hand very many workmen feel contented if they find themselves doing the same amount of work per day as other similar workmen do and yet are getting more pay for it. Employers and workmen alike should look upon both of these conditions with apprehension, as either of them are sure, in the long run, to lead to trouble and loss for both parties.

Through unusual personal influence and energy, or more frequently through especial conditions which are but temporary, such as dull times when there is a surplus of labor, a superintendent may succeed in getting men to work extra hard for ordinary wages. After the men, however, realize that this is the case and an opportunity comes for them to change these conditions, in their reaction against what they believe unjust treatment they are almost sure to lean so far in the other direction as to do an equally great injustice to their employer.

On the other hand, the men who use the opportunity offered by a scarcity of labor to exact wages higher than the average of their class, without doing more than the average work in return, are merely laying up trouble for themselves in the long run. They grow accustomed to a high rate of living and expenditure, and when the inevitable turn comes and they are either thrown out of employment or forced to accept low wages, they are the losers by the whole transaction.

The only condition which contains the elements of stability and permanent satisfaction is that in which both employer and employees are doing as well or better than their competitors are likely to do, and this in nine cases out of ten means high wages and low labor cost, and both parties should be equally anxious for these conditions to prevail. With them the employer can hold his own with his competitors at all times and secure sufficient work to keep his men busy even in dull times. Without them both parties may do well enough in busy times, but both parties are likely to suffer when work becomes scarce.

The possibility of coupling high wages with a low labor cost rests mainly upon the enormous difference between the amount of work which a first-class man can do under favorable circumstances and the work which is actually done by the average man.


Next Section
Difference in Production Quantity between a first class man and an average man - F.W. Taylor



Compare Taylor's management definition with an explanation of lean management. They both mean the same.

"Make decisions that will meet customer expectations at the lowest possible total cost."

in

Building a Lean Fulfillment Stream: rethinking your supply chain and logistics to create maximum value at minimum total cost


– By Robert Martichenko and Kevin von Grabe

– Published May 12, 2010, Lean Enterprise Institute

– Excerpts, author Q & A, bios, more: http://budurl.com/s2au


Robert Martichenko and Kevin von Grabe  say










Updated on  25.8.2022,  21 May 2020,  9 January 2019
Pub on 3 August 2013

New Lean Principles for an Industry 4.0 World

365 Lessons and Case Studies Course on Industrial Engineering - Free Online Lessons - Access and Study.

https://nraoiekc.blogspot.com/2020/05/industrial-engineering-online-course.html



Today I came across an interesting article, "Six Lean Principles for an Industry 4.0 World" Mar 1, 2019, by  Mark Crawford in https://www.asme.org/topics-resources/content/six-new-lean-principles-industry-40-world

The article reports the views expressed by Jim Morgan, senior advisor for product and process development with the Lean Enterprise Institute.  According to Morgan, lean is still about creating exceptional value for the customer (with minimum resources - no muda), but what is new is the growth in  understanding of how to apply lean principles, tools, and practices in new ways in the new technology age. 

The six new principles of focus concepts are given as


1. Gemba (Includes principle of perfection or continuous improvement)

2. Obeya (Cross functional teams for design - we may think of control tower of industry 4.0 systems)

3. Lean Process and Product Development (LPPD)  (Includes earlier lean principles of value, value stream, flow and pull)

        6 LPPD Guiding Principles    https://www.lean.org/the-lean-post/articles/lean-product-process-development-guiding-principles-at-a-glance/

Designing entire value stream; that is, every step required to deliver value to your customer – instead of your product in isolation – is the defining characteristic of LPPD. - Jim Morgan, Lean Enterprise Institute.

https://www.lean.org/the-lean-post/articles/the-6-guiding-principles-of-lean-product-and-process-development/

4. Cellular Manufacturing or Flow Manufacturing (includes principle of flow and pull)

5. 5S

6. Poka Yoke

https://www.asme.org/topics-resources/content/six-new-lean-principles-industry-40-world


Mark Crawford earlier wrote, "5 Lean Principles Every Engineer Should Know" Mar 9, 2016, by Mark Crawford, ASME.org

https://www.asme.org/topics-resources/content/5-lean-principles-every-should-know

The lean principles given by Womack and Jones.

1. Value - F.W. Taylor said, Determine what needs to be done?

2. Value Stream - Process Chart

3. Flow - This is a new emphasis in lean - already in practice through group technology cells

4. Pull - is a new emphasis. Produce as much as possible in response to customer demand even internally within the organization. Like MRP innovation for dependent demand parts, pull principle insists on reducing lead time for internal production and producing as per actuall demand requirement.

5. Perfection - Continuous Improvement - Industrial Engineering (periodic studies and improvement) - Active employee suggestion schemes, improvement circles, shop floor improvement activity.

Three Major Channels of Process Improvement.
1. Process Redesign by Process Planning Team.
2. Process Improvement Study by Industrial Engineering Team.
3. Continuous #Improvement by Involving Shop Floor Employees and All Employees.
Continuous Improvement - Employee Participation Principle of Industrial Engineering


ASME is the birthplace of scientific management and industrial engineering. It is also the organization that gave us the process chart, the main approach for process improvement.

While value stream mapping is given lot of promotion during the recent years, process chart method is the more comprehensive approach and value stream mapping is to be a part of details of process method. This direction is indicated by Womack and Jones in their book "Lean Thinking."

Lean Thinkers have to use Industrial Engineering Tools - especially process charts. [VSM] analysis is at a high level, without many details. To uncover every instance of every type of muda requires a detailed analysis using a portfolio of tools drawn from industrial engineering ... The most important of these are process mapping (to identify and categorize each step together with the time, distance and effort involved)... Womack and Jones, 1996.

Lean Management - Introduction - Evolution.

http://nraoiekc.blogspot.com/2014/02/lean-management.html