Thursday, August 31, 2017

August - Industrial Engineering Knowledge Revision Plan





Revision of Process Industrial Engineering - Methods, Techniques and Tools

In this month's revision plan the focus is on production process improvement which also includes many engineering processes related to production and maintenance of engineering goods and services.

Management of processes are also analyzed and redesigned by industrial engineers. If management processes, activities and policies are responsible for poor productivity, industrial engineers have to propose changes in management methods, practices and tools to improve productivity. This aspect of industrial engineering is discussed under the area - productivity management.

Process Industrial Engineering - Process Efficiency/Productivity Improvement - Process Cost Reduction

First Week

     Process Industrial Engineering
     Machine Tool Improvement and Cutting Time Reduction

     Operation Analysis - Methods Efficiency Engineering
     Operation Analysis Sheet

    Using the Operation Analysis Sheet
    Analysis of Purpose of Operation

    Analysis of All Operations of a Process as a Step of Each Operation Analysis
    Analysis of Tolerances and Inspection Standards

    Analysis of Material in Operation Analysis
    Tool Related Operation Analysis


Second Week

    Material Handling Analysis in Operations
    Operation Analysis of Setups

    Operation Analysis - Man and Machine Activity Charts
    Operation Analysis - Plant Layout Analysis

    Operation Analysis - Analysis of Working Conditions and Method
    Operation Analysis - Common Possibilities for Operation Improvement

    Operation Analysis - Check List
    Method Study

   Principles of Methods Efficiency Engineering
   Method Study - Information Collection and Recording - Chapter Contents


Third Week

Process Analysis - Questions/Check List
Installing Proposed Methods

Eliminate, Combine, Rearrange, Simplify - ECRS Method - Barnes
Process and Productivity Improvement Through Smart Machines and Smart Factories

Process and Productivity Improvement through incorporating Data Analytics
Plant Layout Analysis

Flow Process Charts - Reinterpretation of Its Purpose and Utility
Industrial Engineering of Flow Production Lines - Thought Before Taiichi Ohno and Shigeo Shingo

SMED
Poka-Yoke


Fourth Week

Industrial Engineering - Foundation of Toyota Production System
Toyota Production System Industrial Engineering - Shigeo Shingo

Introducing and Implementing the Toyota Production System - Shiego Shingo
Seven Waste Model and Its Extensions

Industrial Engineering of Maintenance Processes
Manufacturing System Losses Idenfied in TPM Literature

Industrial Engineering of Inspection Processes
Industrial Engineering of Material Handling Processes

Zero Defect Movement and Six Sigma Method
Process Cost Analysis - Cost Center Statement Analysis






One Year Industrial Engineering Knowledge Revision Plan


January - February - March - April - May - June

July - August - September - October - November - December




Updated  30 July 2017,  28 July 2016, 19 April 2015, 17 July 2014


Tuesday, August 29, 2017

Operation Analysis - Methods Efficiency Engineering



Operation Analysis and Method Study are the two popular methods in Process Industrial Engineering. Japanese industrial engineering improvements brought out new techniques like SMED, Poka Yoke, 5S and Seven Waste model etc.

The term 'Operations Analysis" was used by James Anderson in his book on Industrial Engineering published in 1928. He said operation analysis is the short form for long form "Job Standardization, Motion Study and Time Study." H.B. Maynard has authored a full book on operation analysis. The job standardization implies what Taylor did with machine tools before he undertook study of operator's activities and movements.

The First Step


The first step in the study of any process/job is to make a thorough analysis by resolving it into its component parts or elements. Each part or element may then be considered separately, and the study of the process thus becomes a series of fairly simple problems.

A process consists of operations. In process analysis, each operation is examined to rationalize it for doing it as well as doing it at that step in the sequence of operations.  Eliminate, combine, and rearrange (ECR) analysis is done for each operation of the process. In a way, it is an examination of the division of a process into operations to improve the efficiency of the process.

During primary analysis of an operation, the operation is broken down into such general factors as material, inspection requirements, equipment & tools, man  and working conditions. Each one of these factors is then examined minutely and critically in order to discover possibilities for improvement. This kind of analytical work of the operation is covered by the term " operation analysis."

For examining the factors that go into an operation, more detailed methods are available. Motion study, for example,  is 'focused on the method of the operator.

Approach to Operation Analysis


To conduct analysis work successfully, a distinctive mental attitude must be developed. .  In order to improve an operation, it must be approached with the idea that it can be improved. Otherwise, progress is not made in the improvement effort. During the training for operation analysis, number of examples of operation analysis and consequent improvement of the operations have to be given to develop favorable attitude in operation analysts and its team members.

If a job has previously been carefully studied, the best method may conceivably have been devised, and no further improvement may be possible, immediately. Experience has shown, however, that there are few established methods which cannot be improved at a later point in time. In, this connection, the history of a certain bench operation furnishes an excellent and by no means uncommon illustration of this point (Maynard). The job originally was done on daywork, and past production records showed that the time taken per part was 0.0140 hour, or slightly less than 1 minute. The job was time-studied and put on an incentive basis with an allowance of 0.0082 hour. The operator worked made a fair bonus on this job, and the feeling existed for some tune that the proper method was being followed.

After the operation had been set up for 6 months, however, a suggestion for improvement was advanced say by the foreman. The suggestion was not based upon systematic analysis but rather was the result of inspiration. The suggestion was put into effect;  the job was restudied, an allowance of 0.0062 hour was set. This last method was followed for 6 months more, when another suggestion, also of the inspirational type, was advanced. It was adopted, and a new time value of 0.0044 hour was established.

The job was a prominent one, and the improvements attracted considerable attention. The job was selected for detailed motion study. A completely new method was devised which followed the principles of correct motion practices. The new method was time-studied and standard time of 0.0013 hour was set.

The operation was thus improved to an extent where the time required was only approximately one-eleventh of that taken at first on the old daywork basis.   An improvement of such great magnitude justifies the statement that the latest method is a very good method; but in view of the past history of the job, it would be unwise to say that the best method has been attained.

As the result of many similar experiences, methods engineers are using the terms  "the best method yet devised"  implying recognition of the fact that further improvement may be possible (Even Gilbreth stressed this point). Carrying this thought to a logical conclusion, the .best method of doing an operation from a labor-economy standpoint is reached only when the man-machine time required has been reduced to zero. Until this point has been reached, further improvement is always possible.

This example  furnishes a foundation for the approach to operation analysis. If it is clearly recognized, it insures an open mind. Such mental obstacles as "it won't work' "it can't be done" and "it was tried before and didn't work"  are cleared away at the outset. Lack of success in improving any job is not interpreted to mean that the job cannot be improved, but rather that no way of improving it has yet been discovered. There is a vast difference in the two interpretations. The first induces contentment with things as they are and leads to stagnation; the second inspires further attacks from different angles and leads to progress.

The Questioning Attitude.


An open mind paves the way for successful analytical work, but it is not sufficient in itself. One can be open-minded in the passive sense of being receptive to suggestions, but this will not lead to accomplishment. The analyst must take the initiative in originating suggestions himself if he wishes to get results.

Other things being equal, the greatest amount of originality, or what passes for originality in a world where it is often said that there is nothing new, is evinced by those who have an inquiring turn of mind. The man who constantly asks questions and takes nothing for granted is often a disturbance to the contentment of those who are willing to accept things as they are, but he is the one who originates new things. Improvements come from first examining what is with an open mind and then inquiring into what might be.

This point should be clearly understood, and what is known as the " questioning attitude" should conscientiously be developed. In making an investigation of a job, nothing should be taken for granted, and everything should be questioned. Then the answers should be determined on the basis of facts, and the influence of emotions, likes and dislikes, or preconceived prejudices should be guarded against.

One who is successful in bringing about improvements in operating methods has few deep-seated convictions. He accepts little or nothing as being right because it exists. Instead, he asks questions and gathers answers which he evaluates in the light of his knowledge and experience. He questions methods, tools, and layouts. He investigates all phases of every job he studies, in so far, at least, as he has time. He even asks questions when the answers appear obvious, if he thinks he can bring out something by so doing.

The questions asked take the general form of "what," "why," "how," "who," "where," and "when. " What is the operation? Why is it performed? How is it done? Who does it? Where is it done? When is it done in relation to other operations? These questions, in one form or another, should be asked about every factor connected with the job being analyzed. Typical questions that arise during the study of industrial operations are as follows:

If more than one operator is working on the same job, are all operators using the same method? If not, why not? Is the operator comfortable? Sitting down as much as possible? Has the stool or chair being used a comfortable back and a seat that is wide enough? Is the lighting good? Is the temperature of the work station right? Are there no drafts? Are there arm-rests for the operator? If the operation can be done either seated or standing, is the height of the chair such that the elbows of the operator are the same distance from the floor in either case?

Can a fixture be used? Are the position and height of the fixture correct? Is the fixture the best available? Is the fixture designed in accordance with the principles of motion economy? Would a fixture holding more than one piece be better than one holding a single piece? Can the same fixture be used for more than one operation? Can a clamp, a vise, or a fixture be substituted for the human hand for holding? Are semiautomatic tools such as ratchet or power-driven wrenches or screw drivers applicable?

Is the operator using both hands all the time? If so, are the operations symmetrical? Do the hands move simultaneously in opposite directions? Can two pieces be handled at one time to better advantage than one? Can a foot device be arranged so that an operation now performed by hand can be done by foot?

Are raw materials properly placed? Are there racks for pans of material and containers for smaller parts? Can the parts be secured without searching and selecting? Are the most frequently used parts placed in the most convenient location? Are the handling methods and equipment satisfactory? Would a roller or a belt conveyer facilitate handling? Can the parts be placed aside by means of a chute?

Is the design of the apparatus the best from the viewpoint of manufacturing economy? Can the design be changed to facilitate machining or assembly without affecting the quality of the apparatus? Are tools designed so as to insure minimum manipulation time? Can eccentric clamps or ejectors be used?

Is the job on the proper machine? Are the correct feeds and speeds being used? Are the specified tolerances correct for the use to which the part is to be put? Is the material the most economical for the job? Can the operator run more than one machine or perform another operation while the machine is making a cut? Would a bench of special design be bettor than a standard bench? Is the work area properly laid out?

This list of questions could be extended almost indefinitely, but enough have been given to illustrate the sort of questions that should be asked during a methods efficiency study. The importance of asking such questions is paramount. The chief difference between a successful analyst and one who seldom accomplishes
much is that the former has developed the questioning attitude to a high degree. The latter may be capable of making the same improvements as the former, but they do not occur to him as possibilities because he accepts things as they are instead of questioning them.

Operation Analysis Need Not Be Confined to Methods Engineers. Although the questioning attitude is developed by the methods engineer as an aid to thorough analysis, it need not be and should not be solely his property. The other shop supervisors will find it equally useful for attacking their particular problems and finding solutions for them. If they focus it on operating methods, they will be able to make many improvements in the course of their daily work. Thus, methods-improvement work will progress more rapidly than it would if it were left entirely to the methods engineer.

If a plant is small and has insufficient activity to justify employing anyone in the capacity of methods engineer, it will be particularly desirable for all members of the supervisory force to develop the questioning attitude. It is extremely easy to view things without seeing them when they are supposedly familiar. Those most familiar with the work are the least likely to see opportunities for improvement, unless they consciously try to remain as aware of their surroundings as they would be were they new to the plant. Where the supervisory group does not change often, the cultivation of the questioning attitude is almost essential to progress.

Questions should not be asked at random, although this would be better than asking no questions at all. Rather, it is better to proceed systematically, questioning points in the order in which they should be acted upon. It would be unwise, for example, to question the tools, setup, and method used on a certain job before the purpose of the operation was considered. Better tools might be devised, and the method might be changed ; but if it were later found upon examination of the purpose of the operation that it need not be done at all, the time and money spent on tool and methods changes would be wasted.

The systematic job analysis will be discussed in this knol book in sufficient detail to give a thorough understanding.

Making Suggestions for Improvement. 


When a job is examined in all its details with an open mind and when all factors that are related to it are questioned, possibilities for improvement are almost certain to be uncovered if the job has not been studied in this way before. The action that is taken upon the possibilities will depend upon the position of the one who uncovers them. If he has the authority to take action and approve expenditures, he will undoubtedly go ahead and make the improvements without further preliminaries. If, however, he does not have that authority, he must present his ideas in the form of suggestions to the one who does.


In the first place, the true worth of each suggestion should be carefully evaluated before it is offered. If he establishes a reputation for offering only suggestions of real merit, one will find it easier to secure an attentive hearing than if he is continually advancing suggestions that have to be examined to separate the good from the impractical.

The quickest way to prove the merit of any suggestion is to make or obtain estimates of the cost of adopting it and of the total yearly saving it may be expected to effect. These two figures will show just how much must be spent and how long it will be before the expenditure will be returned. If a suggestion costs $1,000 to adopt and will save $100 per year, it is not worth presenting unless there are unusual circumstances. If, on the other hand, the expenditure will be returned within a reasonable length of time, the suggestion is worthy of careful consideration.

When it has been definitely decided that the suggestion is sound and valuable, it should be presented to the proper authorities for approval. Here, again, estimates of expenditure and return will prove valuable. The statement that much time will be saved or even that a saving of 0.0050 hour per piece can be made is not likely to mean so much as figures showing a saving of a certain number of dollars per year. A complete presentation which includes cost and savings totals will be appreciated, for if they are not furnished, they must be requested anyway, and this will only postpone final action.

An example of a good presentation of a labor-saving idea is as follows :

Works Manager:

By analyzing the cork-tube winding operation in the Cork Department, it has been found that one-third of the winder's time is spent in doing work requiring a high degree of skill and the remaining two-thirds in doing work that could be satisfactorily performed by unskilled labor.

The time consumed by the portion of the cycle that requires high skill is almost exactly one-half of that required for the balance. Therefore, it will be entirely feasible to place four winding machines in a group, using one skilled man with two unskilled helpers to run them. In this manner, the average production of three skilled workers running three machines will be obtained at a greatly reduced cost.

Under the proposed setup, the skilled worker will apply the cork to the cloth core which has been set up by one helper and will then move to another machine which the other helper has set up. Each helper will tie the ends of a finished cork-covered tube, will remove the tube, and will set up another while the skilled man is busy at other machines.

The skilled man receives 60 cents per hour and the unskilled men 40 cents per hour each. The labor cost per tube will therefore be approximately 0.76 cent as compared with the present cost of 1 cent each.

On the basis of present activities, this will amount to a yearly saving of $2,361.55. There will be a certain amount of idle machine time under the proposed arrangement; but since we have more machine equipment than we require for our present volume of business, this need not be considered.

This matter has been discussed with the foreman,  and he believes that the arrangement will work satisfactorily. In order to proceed with the proposed change, it will be necessary to relocate 12 machines.  Maintenance Department estimates that this can be done for a cost of $480.

In view of the savings that can be made, the suggestion is recommended for acceptance by you

Signed

In this report, enough details are given to explain the general nature of the suggestion. The total yearly saving of $2,361.55 is shown, as also are the cost of adopting the suggestion and the source of the estimate. The fact that the suggestion meets with the approval of the foreman of the department, always a most important point, is also clearly stated. As a result, all questions that are likely to arise in the mind of the manager are answered in advance, and there is a good likelihood that he will give immediate approval.

Occasionally, ideas occur which appear to possess advantages to the originator other than those which can be measured in dollars and cents. In presenting suggestions of this nature, advantages and disadvantages should be presented in tabulated form, so that a decision can be quickly made.


Source: Maynard's Operation Analysis

Full Knol Book - Method Study: Methods Efficiency Engineering - Knol Book
Next Article on the Topic - Scope and Limitations of Methods Efficiency Engineering



Process analysis is an examination of the division of a process into operations to improve the efficiency of the process. Process analysis examines the sequence of steps specified to convert inputs into outputs.

Process analysis now is extended to analyzing the process in other dimensions.



Journal of Intelligent Manufacturing
October 2006, Volume 17, Issue 5, pp 571-583
Evaluation of techniques for manufacturing process analysis
J. C. Hernandez-Matias, A. Vizan, A. Hidalgo, J. Rios
http://link.springer.com/article/10.1007%2Fs10845-006-0025-1


Updated 30 July 2017,  28 June 2015
First posted 16 Feb 2014

Tuesday, August 15, 2017

Data Analytics Period in Productivity Improvement - Productivity Engineering and Management






2016

The wave of productivity driven by data and analytics - McKinsey senior partners


"You had the wave of lean, you had the wave of outsourcing, and now we’re seeing the wave of productivity driven by data and analytics, enabling organizations to refine the way that people work together, the way that processes perform, and the way assets are productive. If you think about an oil well, for example, you’ve got more than 300 sensors downhole that are spewing out data at the rate of about a gigabit a second, in some cases." - Bill Wiseman, McKinsey senior partner

How advanced analytics can drive productivity
Podcast August 2016
Podcast transcript
http://www.mckinsey.com/business-functions/mckinsey-analytics/our-insights/how-advanced-analytics-can-drive-productivity

How Data Analytics Increases Productivity?


Technology and innovation drive productivity.  But transaction costs of new technology implementation are considerable.  Innovation requires capital and labor investment incurring transaction costs to build infrastructure and grow the market.

Analytics and decision science could provide the means to reduce the transaction costs and increase innovations to  improve productivity in the economy.

Analytics provide a process to monitor, measure, and benchmark performance. By integrating diverse datasets from remote monitoring (IoT), measuring, and benchmarking can be accomplished automatically and economically. Reporting by anomaly and exception could free resources and thereby reduce costs and improve productivity.

Application of analytics to monitoring energy through sensors resulted in 17% reduction in energy costs for the NJ DOT main office complex. In another application, propensity models were constructed from customer profile and behavior data to identify candidates with highest conversion rates for sending sales promotion communications. Such examples are now many, to illustrate applying analytics to reduce costs and improve operations.

Low cost cloud computing together with large, diverse, and growing datasets, from the web to internal sources, and available statistical visualization tools, have dramatically changed the cost of data analytics. The low cost of data analytics is allowing more companies to use analytics and improve the productivity.

Source: Onoly Analytics and Analytics 2 Insight - White Paper
Analytics at the Speed of Insight: Simple, Fast and Actionable Tools to Improve Productivity


-------------------------------------------------------------------------

Further Developments


2017


Be agile, Be focused on results and Take up manageable data analytics projects
https://www.bcg.com/publications/2017/digital-transformation-transformation-data-driven-transformation.aspx

Digital transformation-driven productivity
Don't underestimate the incredible power of DX turned inward, toward enhancing internal organizational productivity.
http://www.cio.com/article/3200807/leadership-management/digital-transformation-driven-productivity.html

Digital Transformation Can Resolve the Productivity Paradox
EITN MALAYSIA, April 27, 2017
By Hu Yoshida, Chief Technology Officer, Hitachi Data Systems
http://www.enterpriseitnews.com.my/digital-transformation-can-resolve-the-productivity-paradox/

How digital transformation improves productivity in manufacturing
By Alex Walker and Arnd Simon, Senior Directors, Industry Services, Global Manufacturing Practice, Microsoft Corporation; Contributor: Dr. Lei Liu, Digital Advisor, Microsoft Deutschland GmbH on May 5, 2017
https://enterprise.microsoft.com/en-us/articles/industries/discrete-manufacturing/digital-transformation-improves-productivity-manufacturing/

Increasing Chemical Industry Productivity through Digital Transformation

May 12, 2017 | Showcase
Learn how Capgemini's ChemPath SAP – Certified Business All-in-One (BAIO) solution, will help your organization streamline and synchronize the operations, while achieving greater visibility and control over your core business processes.
https://www.capgemini.com/resources/video/increasing-chemical-industry-productivity-through-digital-transformation

IoT use cases with 2 year pay back period in global auto company mentioned.
https://www.linkedin.com/pulse/chinas-factories-want-digitize-heres-what-need-do-karel-eloot

Microsoft Workplace Analytics helps managers understand worker productivity
https://techcrunch.com/2017/07/05/microsoft-workplace-analytics-helps-managers-understand-worker-productivity/


2016


EXPLORING THE POTENTIAL OF DATA DRIVEN AGRICULTURE IN INCREASING FARM PRODUCTIVITY AND PROFITABILITY

November 2016

Smart data is the way to boost mining productivity

2 September 2016
https://home.kpmg.com/xx/en/home/insights/2016/09/smart-data-way-boost-mining-productivity.html

Improving dragline productivity and increasing reliability using big data

August 2016

Mining operations produce an enormous amount of data through numerous parallel, though diverse, monitoring systems. Data mining and analytics can be a major part of a successful mining improvement process.

In this case, the goal is to find a single target variable and its value that will drive operator behaviour to operate the dragline at maximum production capacity and speed while not exceeding machine fatigue.
https://www.ausimmbulletin.com/feature/improving-dragline-productivity-and-increasing-reliability-using-big-data/

2015


Production Data Analytics – To identify productivity potentials
Master Thesis - 2015
MUKUND SUBRAMANIYAN
Department of Product and Production Development
CHALMERS UNIVERSITY OF TECHNOLOGY, Gothenburg, Sweden - 2015
http://publications.lib.chalmers.se/records/fulltext/225149/225149.pdf


2013


Data Analytics and Continuous Productivity
September 18, 2013
https://www.tibco.com/blog/2013/09/18/data-analytics-and-continuous-productivity/


July 2013

Big-data analytics as a productivity tool McKinsey Global Institute


Sectors across the economy can harness the deluge of data generated by transactions, medical and legal records, videos, and social technologies, sensors, cameras, bar codes, and transmitters embedded in the world around us. Advances in computing and analytics can transform this sea of data into insights that create operational efficiencies.

By 2020, the wider adoption of big-data analytics could increase annual GDP in retailing and manufacturing by up to $325 billion.

Additionally as much as $285 billion savings can occur in the cost of health care and government services.

http://www.mckinsey.com/global-themes/americas/us-game-changers


2011

MIT professor Erik Brynjolfsson discusses how companies can increase their productivity by making better use of their data.
by David Talbot  February 16, 2011
https://www.technologyreview.com/s/422753/using-it-to-drive-innovation/


2009
MIT professor Erik Brynjolfsson
Book Chapter: Business practices that enhance productivity along with IT investments.
https://books.google.co.in/books?id=WBYeChNzVo8C&pg=PA61#v=onepage&q&f=false




Updated  16 August 2017,  10 July 2017,  30 June 2017, 22 June 2017


Productivity Improvement Through Smart Machines



IIOT, Industry 4.0, 4IR (Fourth industrial revolution) etc. are  frameworks to merge the operational technology (OT) with the information technology (IT) to provide new solutions for automating and networking industrial machines and systems for performance and productivity improvement.

What is a Smart Machine?

It is self-­aware, reacts autonomously and provides information about the product being produced, production parameters utilized, production time taken production quantity in unit time periods, production history,  configuration, condition, quality and Overall Equipment Efficiency (OEE) to other machines.

Smart Machine Control
Machine vision and advanced motion control are key components of smart automation. Engineers can increase throughput and build highly efficient modern machines that sharpen accuracy and easily adapt to new products and processes.

Today, the keys to smart machine control are gaining insight into the machine’s operation and the ability to adjust control outputs. Engineers rely on sensor information to monitor the condition of mechanical parts, which gives them the ability to observe the process for quality control or closed-control loops for applications like force feedback or precise positioning.

Today, LabVIEW (of NI.Com) graphical programming helps leading machine builders master this increasing system complexity with add-on modules for motion control, machine vision, and control design and simulation.


2017

Leonardo Smart Rotational Moulding Machine
http://www.leonardosmart.com/

Smart Machine
Bringing intelligence into the milling process is the intended aim of "smart machine".

Optimization of the Machining Process

http://www.gfms.com/country_US/en/Products/Milling/smart-machine/oss.html

Patented: The Original OSS
The intelligent Operator Support System optimises the machining process according to the specifications of the workpiece. The target variables – speed, accuracy and surface quality – as well as the workpiece weight and the complexity of the machining application can be selectively defined and modified at any time via an intuitive user interface.

Setting priorities
The user can define the machine settings via the OSS, depending on the operation. He can choose from 12 predefined settings or extend them as desired.

Priority: Time

Only the time is of interest when roughing. If the operator selects the time as the highest priority, then OSS extends the tolerance band. In addition to this, the control system adapts the speed profile to the geometry that is to be processed.

Priority: Surface quality

In order to maintain the best possible surface quality despite poor NC program quality, the tolerance band is enlarged and the transitions are smoothed

Priority: Accuracy

If the workpiece demands extremely high precision, the tolerance band selected is narrower, in order to achieve the required accuracy. The control system is configured in such a way that the best possible geometrical accuracy is guaranteed.

User-defined setting

Additional settings can be saved in a library and can then be used again at any time. Several positions can be selected between the extremes (surface quality, accuracy, time).

Productivity & Precision

Your benefit
The intelligent system sets the dynamic behaviour of the machine exactly according to the workpiece requirements
Shorter machining times
Better surface quality
Intuitive handling of complex settings
Reduced complexity when setting up a workpiece
http://www.gfms.com/country_US/en/Products/Milling/smart-machine.html

2016

Cat (Caterpillar) Connect Technology: Hardware and software available for equipment to arm customers with information designed to help them optimize their operations. Specific construction technologies include:

        o  LINK, a solution that captures vital performance and product health data and makes that data available on the web to guide decision-making.

        o  GRADE and COMPACT, two productivity solutions that help operators move material faster, more accurately and with fewer passes.

        o  PAYLOAD, an on-board system for trucks and loading tools that drives higher efficiency, shorter cycle times and lower cost per ton.

http://www.caterpillar.com/en/news/corporate-press-releases/h/caterpillar-introduces-the-age-of-smart-iron-digital-technology-designed-to-transform-productivity-efficiency-and-safety-on-job-sites.html

Smart Asphalt Compaction


______________

______________
Catpaving
Caterpillar’s new B-Series tandem vibratory asphalt roller models include a range of advancements in intelligent compaction technology to deliver higher quality compaction. These models — the CB64B, CB66B, and CB68B — feature technological improvements made possible through Cat Compaction Control, Caterpillar’s intelligent compaction suite. The suite consists of dual air-purged, infrared temperature sensors that are integrated into the front and rear of the machine.
http://www.government-fleet.com/channel/equipment/article/story/2016/02/caterpillar-rolls-toward-smarter-asphalt-compaction.aspx


2015

Smart Food Processing


A Cisco project involving Sugar Creek Packing Co. , Washington Court House, Ohio is making machines and processes smarter. The company recently commissioned a brownfield project in Cambridge City, Ind., Harvesting large amounts of data and feeding it back as actionable information is used for  for establishing a high-performance work team structure at the plant. “High-performance work teams are semi-autonomous teams work with little supervision, with production, maintenance and HR issues handled by team members. They need meaningful feedback and they get it from the smart features of the system. A sous vide cooking system is an illustration of it. It is a disruptive cooking technology and a highly automated system, with hundreds of sensors to control the process. To access the data, team members use a Cisco mobile app called Jabber, “essentially an IP phone. This feature substitutes installing the system based on ordinary mobiles with a booster system that would have added $300-500 million to project cost. Jabber radios essentially function like a desk phone and integrate easily with plant software. The wireless network also will track worker locations within one meter via RFID tags embedded on protective headgear.

http://www.foodprocessing.com/articles/2015/plant-automation/?start=0


2014

“Smart” ProSlab 155 Automated Turf Harvester

National Instruments Corporation, Austin, Texas describes the machine as smart machine.

The machine uses LabVIEW software and CompactRIO hardware supplied by National Instruments. The smart machine harvests turf 20 percent faster, and uses half the diesel fuel than other turf harvesting machines on the market. It uses more electric systems. FireFly engineers can also remotely monitor, diagnose, update (and control) the sensor-laden ProSlab 155

http://fireflyequipment.com/proslab-155/

http://sine.ni.com/cs/app/doc/p/id/cs-16758
________________

________________


2013

The technologies for building a large-scale and diverse scope of smart machines are coalescing and being tested by "first movers." Once they offer significant  cost reduction and productivity improvement, companies will embrace them by employing smart machines in place of humans.

IT cost is typically about four percent of annual revenue of the companies, whereas the labor costs that can be rationalized by smart machines are as high as 40 percent of revenue in some knowledge and service industries. This gives considerable scope for deploying further IT systems.

The firms that have not begun to develop programs and policies for a "digital workforce" by 2015 will not perform in the top quartile for productivity and operating profit margin improvement in their industry by 2020. As a direct result, the careers of CIOs who do not begin to champion digital workforce initiatives with their peers in the C-suite by 2015 will be cut short by 2023.

http://www.gartner.com/newsroom/id/2605015


Books on Smart Machines


Manufacturing Intelligence for Industrial Engineering: Methods for System Self-Organization, Learning, and Adaptation: Methods for System Self-Organization, Learning, and Adaptation

Zhou, Zude
IGI Global, 31-Mar-2010 - Computers - 407 pages

The manufacturing industry has experienced dramatic change over the years with growing advancements, implementations, and applications in technology.

Manufacturing Intelligence for Industrial Engineering: Methods for System Self-Organization, Learning, and Adaptation focuses on the latest innovations for developing, describing, integrating, sharing, and processing intelligent activities in the process of manufacturing in engineering. Containing research from leading international experts, this publication provides readers with scientific foundations, theories, and key technologies of manufacturing intelligence.
https://books.google.co.in/books?id=aejvZWm2_a8C

Manufacturing in Real Time: Managers, Engineers and an Age of Smart Machines

Gian F. Frontini, Scott Kennedy, Scott L. Kennedy
Butterworth-Heinemann, 2003 - Business & Economics - 206 pages

The development of self-operating machines is the foundation of modern manufacturing. This current manufacturing environment is based on automation and smart machines that have the ability to make things with a level of accuracy and consistency that humans cannot match. In order to maximize efficiency, engineers and managers need to change their outlooks, processes and strategies and as a result, adopt new methods and management systems.

The authors demonstrate what is needed by first presenting a brief history of manufacturing and the changes we have already seen and then make their way into the current manufacturing environment. Topics covered include supply chain management, product streams, the role of automation in the supply chain, the relationships between machines and people in automated product streams (looking at what machines do best and what humans do best), variation and quality control, statistical process control, the flow of information in a supply chain and how all of these elements are effected by new technologies and need to be changed to allow for maximum efficiency as we move more toward automation in factories.

*Discover the impact of new technologies on the future shape on the manufacturing industry
*Excellent examples used throughout to demonstrate each idea and process
*Includes a CD with lectures, slides, tutorials, dynamic models and much more!
https://books.google.co.in/books?id=Cx0YriQ-7owC


Bibliography

http://www.schneider-electric.co.uk/en/download/document/170226-MSol-thought-leadership/

http://www.ni.com/en-in/innovations/transportation-and-heavy-equipment/smart-machine-control.html


High Productivity Through Smart Factories



Updated 16 August 2017, 13 July 2017

Sunday, August 13, 2017

Process Analysis - Questions/Check List




Book: Productivity Through Process Analysis by Jinichi Ishiwata
Four basic principles for process improvements
1. Eliminate processes whenever possible.
2. Simplify them. (Operations analysis)
3. Combine them
4. Change the sequence
Questions
1. Eliminate  - Can this be eliminated? What will happen if we eliminate it?
2. Simplify - Can this made simpler?  - the task of operations analysis
3. Combine - Can two or more processes be consolidated into one?
4. Change sequence - Can this operation be switched with another one?
Big three problems in process: waste, irrationality, and inconsistency
5W1 Analysis for Product Process Analysis
Operation - Why - Who is doing it - Which machine - where - when - How
Can the layout be changed to reduce the transportation?
Can number of inspections be reduced?
Are any inspections unnecessary?
Can necessary inspections be done while the product is being processed?
Can number of delays be reduced?
Book: Motion and Time Study - Improving Productivity by Marvin E. Mundel
Checklist for Process Chart - Product Analysis
basic principles
1. Reduce number of steps.
2. Arrange steps in best order.
3. Make steps as economical as possible (operation analysis).
4. Reduce handling.
5. Combine steps if economical.
6. Shorten moves.
7. Provide most economical means for moving (operation analysis)
8. Cut in-process inventory to workable minimum
9. Use minimum number of control points at most advantageous places
Questions
1. Can any step be eliminated?

a. as unnecessary. (Ask: Why is it done?)
b. By new equipment (Ask: Why is present equipment used?)
c. By changing the place where it is done or kept. (Ask: Why is it done there?)
d. By changing the order of work. (Ask: Why is it done in its present order?)
e. By changing the product design. (Ask: Why is it made as it is?)
f. By changing the specifications of the incoming supply. (Ask:  Why is it ordered in its present form or used at all)
2. Can any step be combined with another?

a. By changing the specifications of supplies, or of any raw material?
b. By changing the design of the product, even if only the tolerances?
c. By changing the order of the steps of production, or doing inspection at any operation station so as to avoid an inventory of faulty product?
d. By changing the equipment used (e.g., using a multifunction machine, or creating a multimachine work cell served by a single person or by a robot)/
e. By redesigning one or more work places?
3. Can steps be rearranged so as to make any shorter or easier?
4. Can any step be made easier?
Book: Motion and Time Study: Design and Measurement of Work by Ralph M. Barnes
Following approaches should be considered in developing preferred work method
A. Eliminate all unnecessary work.
B. Combine operations or elements.
C. Change the sequence of operations
D. Simplify the necessary operations



Process Analysis, Process Improvement, and Cost Reduction
____________________

____________________
rtdknowledge


Updated  15 August 2017, 10 February 2012

Saturday, August 5, 2017

Cloud Computing - Productivity Science



Ozdemir A, Asil H (2017)
The Optimization of Query Processing in Sea Base Cloud Databases Based on CCEVP Model.
Ind Eng Manage 6:208. doi:10.4172/2169-0316.1000208

The increase in data volume in many applications and the need for their calculations are the database challenges. Cloud computing and the use of Sea Base databases are a solution to integrate a variety of DBMSs and integrated access to tables in databases. The study tried to optimize query processing in the Sea Base cloud database and reduce query processing time. The method used adaptability for optimization. The purpose of this method is to make adaptive the execution plans of high-traffic queries sent to the Sea Base. For adaptability, the method uses three parts: separator, similarity detector and replacement policy.  The results show that the system optimizes query processing in the database and reduces response time by one percent. The response time can be further decreased by changing the replacement policy.

https://www.omicsgroup.org/journals/the-optimization-of-query-processing-in-sea-base-cloud-databases-basedon-ccevp-model-2169-0316-1000208.php?aid=86516

Productivity - Journals




Journal of Productivity Analysis
https://link.springer.com/journal/11123

International Journal of Productivity and Quality Management
http://www.inderscience.com/jhome.php?jcode=ijpqm

International Journal of Productivity and Performance Management
ISSN: 1741-0401
Previously published as: Work Study
http://www.emeraldinsight.com/toc/ijppm/66/6

Journal of Productivity Analysis
https://ideas.repec.org/s/kap/jproda.html

International Journal of Productivity Management and Assessment Technologies (IJPMAT)
https://www.igi-global.com/journal/international-journal-productivity-management-assessment/45937

Friday, August 4, 2017

Industrial Engineering Journals


Ranking of Journals in Industrial and Manufacturing Engineering
http://www.scimagojr.com/journalrank.php?category=2209


Journal of Industrial Engineering International

Journal of Industrial Engineering International  is a peer-reviewed open access journal published under the brand SpringerOpen, covering all aspects of industrial engineering. It is fully supported by the Islamic Azad University, who provide funds to cover all costs of publication, including the Article Processing Charges (APC’s) for all authors. Therefore the journal is both free to read and free to publish in.
http://www.springer.com/engineering/production+engineering/journal/40092


Journal of Industrial and Production Engineering

Official Journal of the Chinese Institute of Industrial Engineers
http://www.scimagojr.com/journalsearch.php?q=21100241791&tip=sid&clean=0
Volume 32, Issue 2, 2015
http://www.tandfonline.com/toc/tjci21/current#.VScvHtyUd1Y


International Journal of Applied Industrial Engineering (IJAIE)

Editor-in-Chief: Lanndon Ocampo (University of the Philippines Cebu, Philippines)
Indexed In: INSPEC and 10 more indices
Published: Semi-Annually |Established: 2012

Topics Covered
Business and strategy
Case studies in industry and services
Decision analysis
Engineering economy and cost estimation
Enterprise resource planning and ERPII
Facility location, layout, design, and materials handling
Forecasting, production planning, and control
Human factors, ergonomics, and safety
Industrial engineering education
Information and communication technology and systems
Innovation, knowledge management, and organizational learning
Inventory, logistics, and transportation
Knowledge and technology transfers in a globalized network
Manufacturing, control, and automation
Operations management
Performance analysis
Product and process design and management
Project Management
Purchasing and procurement
Reliability and maintenance engineering
Scheduling in industry and service
Service systems and service management
Supply chain management
Systems and service modeling and simulation
Technology transfer and management
Third party/fourth party logistics
Total quality management and quality engineering

https://www.igi-global.com/journal/international-journal-applied-industrial-engineering/41034


European Journal of Industrial Engineering
http://www.scimagojr.com/journalsearch.php?q=11200153401&tip=sid&clean=0


International Journal of Industrial Engineering Computations
http://www.scimagojr.com/journalsearch.php?q=21100223326&tip=sid&clean=0

International Journal of Industrial and Systems Engineering
http://www.scimagojr.com/journalsearch.php?q=5800179616&tip=sid&clean=0

Journal of Industrial Engineering and Management
http://www.scimagojr.com/journalsearch.php?q=19700188349&tip=sid&clean=0

International Journal of Industrial Engineering : Theory Applications and Practice
http://www.scimagojr.com/journalsearch.php?q=19151&tip=sid&clean=0

South African Journal of Industrial Engineering
http://www.scimagojr.com/journalsearch.php?q=19700173182&tip=sid&clean=0

Jordan Journal of Mechanical and Industrial Engineering
http://www.scimagojr.com/journalsearch.php?q=20000195025&tip=sid&clean=0

International Journal of Industrial Engineering and Management
http://www.scimagojr.com/journalsearch.php?q=21100211751&tip=sid&clean=0

Journal of Japan Industrial Management Association
http://www.scimagojr.com/journalsearch.php?q=144786&tip=sid&clean=0

Engineering Optimization
http://www.scimagojr.com/journalsearch.php?q=29114&tip=sid&clean=0


Updated  5 August 2017, 18 June 2017, 9 April 2015

General - System Level Productivity Science


2017

FEBRUARY 16, 2017 by Jaap Backx, Christoph Hilberath, Reinhard Messenböck, Yves Morieux, and Henning Streubel
BCG Perspectives

Businesses compete in a world that is growing ever more complex. Disruptive technologies emerge with increasing frequency. Customers’ needs and demands change at breakneck speed. New competitors are always entering the fray.

In their attempts to reduce uncertainty and reestablish control amid this new complexity, companies tend to introduce new reports, new rules, and new processes. Such reactions, however, simply translate external complexity into internal “complicatedness”—the counterproductive proliferation of cumbersome structures, processes, and systems. Complicatedness hinders productivity by creating a work environment that leaves employees disengaged and unmotivated.

https://www.bcgperspectives.com/content/articles/people-organization-operations-mastering-complexity-through-simplification/

3D Printing - Additive Manufacturing - Productivity Science and Engineering





Igor Yadroitsev, Ina Yadroitsava, Philippe Bertrand, Igor Smurov, (2012) "Factor analysis of selective laser melting process parameters and geometrical characteristics of synthesized single tracks", Rapid Prototyping Journal, Vol. 18 Issue: 3, pp.201-208, https://doi.org/10.1108/13552541211218117

http://www.emeraldinsight.com/doi/abs/10.1108/13552541211218117


Paper available for review in the Google Book

https://books.google.co.in/books?id=tMndCgAAQBAJ&pg=PA121#v=onepage&q&f=false


Nowadays to increase productivity of SLM process, high laser power up to 400 W and high scanning speed up to 3 m/s are used.

Smaller thickness of layer allows for better accuracy of the manufactured part. But increases manufacturing time. (page 122 of the book)

Knowledge Worker Productivity - Productivity Science


2017


Margaret Moussa, Mathew Bright, Maria Estela Varua, (2017) "Investigating knowledge workers’ productivity using work design theory", International Journal of Productivity and Performance Management, Vol. 66 Issue: 6, pp.822-834.

The paper concludes by offering suggestions for a model suitable for examining the drivers of knowledge work productivity.

Survey instruments based on the recommended model potentially provide a valuable means for understanding and enhancing productivity in a variety of knowledge intensive service industries. The pronounced benefit of this model is that it is applicable in cross-industry and cross-occupational contexts, unlike many existing knowledge worker productivity models.
https://doi.org/10.1108/IJPPM-08-2016-0161


2013

Peter F. Drucker gave a call for knowledge worker productivity.

Can IEs do some things in that area?

http://www.iiewest.org/2013/02/clarion-call-to-ies-lets-improve-knowledge-worker-productivity/


Raise the productivity of interaction workers—high-skill knowledge workers, including managers and professionals—by 20 to 25 percent by using social technologies internally and externally.


Updated 5 August 2017, 6 August 2013

Manufacturing System Digital Transformation and Reengineering





Information technology was applied with significant effect in business processes and during that phase of progress Business Process Reengineering (BPR) emerged as an important method. In manufacturing CNC, CAD-CAM, and CIM appeared. But the current development Internet of Things (IoT) seems to having a major impact on the manufacturing systems. It is getting the description of Industrial Revolution 4.0.

In Industrial engineering also, we can see IE 1.0 - Science of Man - Machine Systems (From Taylor to Taiichi Ohno), IE 2.0 - Low Inventory Manufacturing (Taiichi Ohno, Shigeo Shingo to Womack et al.) and IE 3.0 - Imaginative Use of New Technology by Understanding the Power of the Technology First (Michael Hammer, Thomas Davenport to current days).

Will IE 4.0 be driven by innovations by Industrial Engineers in the age of Digital Transformation of Manufacturing Processes?

Presently number of papers are being published by leading consultants to make digital transformation a big movement.  Their references are being collection in this post








2017
March 2017

By 2018, 60 percent of the large manufacturers will bring in new revenue from information based products and services.

By 2020, manufacturers will claim 20% more after market revenue by offering more services through information (IoT) based support.
https://www.i-scoop.eu/digital-transformation/digital-transformation-manufacturing/



2016

October 2016
IDC - Dassault Research Paper on Status of Industry 4.0 in Germany
https://www.3ds.com/megatrends/manufacturing/from-vision-to-reality-industry-4-0/

April 2016

The Digital Transformation Playbook: Rethink Your Business for the Digital Age

By David Rogers
2016
Columbia University
https://books.google.co.in/books?id=LsF1CwAAQBAJ&printsec=frontcover#v=onepage&q&f=false


February 2016
Industry 4.0.
DIRECTORATE GENERAL FOR INTERNAL POLICIES
POLICY DEPARTMENT A: ECONOMIC AND SCIENTIFIC
POLICY
European Parliament

This study, prepared by Policy Department A at the request of the ITRE
committee, analyses the Industry 4.0 Initiative which encompasses the
digitalisation of production processes based on devices autonomously
communicating with each other along the value chain. It considers the potential of
the initiative and business paradigm changes and impacts of this transformation.
The study assesses the rationale for public intervention and outlines measures
that could be adopted to increase the gains and limit the threats from Industry
4.0.
http://www.europarl.europa.eu/RegData/etudes/STUD/2016/570007/IPOL_STU(2016)570007_EN.pdf

January 2016

EXAMPLES DIGITAL TRANSFORMATION 

Good number of examples (21) with source indicated for more information
http://www.boardofinnovation.com/digital-transformation-examples/



Digital Futures, Digital Transformation - From Lean Production to Acceluction


Authors: Bounfour, Ahmed
Copyright - 2016, Publisher: Springer International Publishing
This book provides an integrated overview of key trends in digital transformation, taking into consideration five interrelated dimensions: strategy and business models, society, organization, technology and regulation. As such, it provides a framework for the analysis of digital business transformation and its emerging factors, analyzing twenty-five key trends in terms of their future impact. On that basis, the book then delineates a new approach centered on the mutually accelerating links between multiple value creation spaces. It proposes a new mode of production – accelerated production of links (acceluction) – and analyzes it with respect to the still-dominant concept of lean production. Based on the results of the international CIGREF research program ISD, the book presents a valuable perspective of the expected impact of the abundance of networks and data as critical resources for enterprises beyond 2020.
http://www.springer.com/us/book/9783319232782

Digital Transformation of the Firm: New Strategies, New Structures

Jan 2016
http://knowledge.wharton.upenn.edu/article/digital-transformation-firm-new-strategies-new-structures/


2015


Boosting Visibility, Agility and Profits with Digital Manufacturing

Digital Transformation: What It Means to Manufacturers

Cisco white Paper

http://www.cisco.com/c/dam/en/us/solutions/collateral/industry-solutions/C11-735848.pdf


UNLOCK CAPITAL AND TRANSFORM BUSINESS MODELS

DIGITAL TRANSFORMATION FOR MANUFACTURING

CSC - Computer Sciences Corporation

http://assets1.csc.com/manufacturing/downloads/Digital_Transformation_Solution.pdf


Industry 4.0

Challenges and Solutions for the Digital Transformation and the Use of Exponential Technologies

Deloitte

Survey of more than 50 companies in Switzerland
http://www2.deloitte.com/content/dam/Deloitte/ch/Documents/manufacturing/ch-en-manufacturing-industry-4-0-24102014.pdf


How to Become a Digital Leader

Arthur D Little

67 Pages Report
http://www.adlittle.de/uploads/tx_extthoughtleadership/ADL_HowtoBecomeDigitalLeader_01.pdf

September 2015

Mercedes-Benz as pioneer of the digital transformation: From Car Manufacturer to Networked Mobility Service Provider

Daimler AG Media Release

Detailed the initiatives at various stages in the manufacturing system and product
https://media.daimler.com/dcmedia/0-921-1845911-1-1847484-1-0-0-0-0-0-0-0-0-1-0-0-0-0-0.html



How Five Companies Launched Digital Transformations

SEPTEMBER 01, 2015 by Lars Fæste, Thomas Gumsheimer, and Matthias Scherer

BCG

https://www.bcgperspectives.com/content/articles/transformation-large-scale-change-technology-business-transformation-five-companies-launched-digital-transformations/


Man and Machine in Industry 4.0

How Will Technology Transform the Industrial Workforce Through 2025?

BCG

SEPTEMBER 28, 2015
https://www.bcgperspectives.com/content/articles/technology-business-transformation-engineered-products-infrastructure-man-machine-industry-4/


June 2015

Manufacturing’s next act

By Cornelius Baur and Dominik Wee
Industry 4.0 is more than just a flashy catchphrase. A confluence of trends and technologies promises to reshape the way things are made.

McKinsey


We define Industry 4.0 as the next phase in the digitization of the manufacturing sector, driven by four disruptions:
- the astonishing rise in data volumes, computational power, and connectivity, especially new low-power wide-area networks;
- the emergence of analytics and business-intelligence capabilities;
- new forms of human-machine interaction such as touch interfaces and augmented-reality systems;  and
- improvements in transferring digital instructions to the physical world, such as advanced robotics and 3-D printing.
http://www.mckinsey.com/business-functions/operations/our-insights/manufacturings-next-act


May 2015

Industry 4.0: It's all about information technology this time
The so-called Industry 4.0 concept now being embraced in Europe predicts the Internet of Things will change manufacturing as we know it.
http://www.zdnet.com/article/industry-4-0-its-all-about-information-technology/


Industry 4.0: The Future of Productivity and Growth in Manufacturing Industries

BCG

The Nine Pillars of Technological Advancement

Big Data and Analytics
Autonomous Robots
Simulation
Horizontal and Vertical System Integration
The Industrial Internet of Things
Cybersecurity
The Cloud
Additive Manufacturing
Augmented Reality
https://www.bcgperspectives.com/content/articles/engineered_products_project_business_industry_40_future_productivity_growth_manufacturing_industries/?chapter=2#chapter2

February


Revamping Your Business Through Digital Transformation
MIT Sloan Management Review, Magazine: Spring 2015, Research Highlight February 18, 2015  Reading Time: 11 min
George Westerman and Didier Bonnet
http://sloanreview.mit.edu/article/revamping-your-business-through-digital-transformation/


First iOS Apps from Apple-IBM venture
January 5th, 2015
https://blogs.perficient.com/digitaltransformation/2015/01/05/first-ios-apps-from-apple-ibm-venture/


Updated 5 August 2017,  12 March 2017, 18 April 2016.

Thursday, August 3, 2017

Robots and Cost Reduction


2017

ABB Frosinone - Collaborative Robotics: more products, more work
2017-07-20 - A textbook example of how Industry 4.0 at an ABB plant in Italy has brought greater employment and production.
http://www.abb.com/cawp/seitp202/BF4B589876268CA6C125814F004DEEDC.aspx

What Is the Real Cost of an Industrial Robot Arm?
Ken Thayer
27 April 2017
Labor cost savings due to Robot use is given for many countries in the year 2025.
http://insights.globalspec.com/article/4788/what-is-the-real-cost-of-an-industrial-robot-arm


The Robotmakers – Yesterday, Today and Tomorrow
by Tanya M. Anandan, Contributing Editor
Robotic Industries Association
POSTED 04/28/2017
https://www.robotics.org/content-detail.cfm/Industrial-Robotics-Industry-Insights/The-Robotmakers-Yesterday-Today-and-Tomorrow/content_id/6513

2016

Reduction of Robot Price

The cost to purchase and implement a robotic spot welder has plummeted from $183,000 in 2005 to $132,000 in 2014, with the price forecasted to drop another 22% by 2025, according to Technavio’s lead industrial automation analysts.

In computer electronics manufacturing, it costs $4 per hour to use a robot for a routine assembly task compared to $24 for an average worker. In the US, industrial robots in auto manufacturing are already operating at a cost of $7.25 hourly wage after the cost of the robot is recovered. For example: the Baxter collaborative robot from Rethink Robotics, which works alongside the human workforce on the factory floor, only costs $22,000.
https://www.technavio.com/blog/industrial-robots-united-states-cut-labor-costs-21-2020


At Ford's factory in Cologne, Germany,  collaborative robots, or co-bots are working side by side with 4,000 Ford factory workers.

Automakers are leading the way in the adoption of co-bots, which they say are more cost-effective than industrial robots. The average selling price of a co-bot is close to $30,000, a number expected to drop to $18,500 by 2020. Automakers prefer the flexibility that comes with co-bots, which can work without safety cages and therefore can be rolled around to different parts of the factory.
https://www.cnbc.com/2016/10/31/ford-uses-co-bots-and-factory-workers-at-its-cologne-fiesta-plant.html


2015
Robotics systems are becoming an economically viable alternative to human labor in more and more industries. A human welder today earns around $25 per hour (including benefits), while the equivalent operating cost per hour for a robot is around $8 when installation, maintenance, and the operating costs of all hardware, software, and peripherals are amortized over a five-year depreciation period. In 15 years (by 2030), that gap will widen even more dramatically. The operating cost per hour for a robot doing similar welding tasks could plunge to as little as $2 when improvements in its performance are factored in.
https://www.bcgperspectives.com/content/articles/lean-manufacturing-innovation-robots-redefine-competitiveness/




Justifying the Cost of a Robotic Welding System
http://www.lincolnelectric.com/assets/US/EN/literature/mc04179.pdf
Robots in packaging: It’s all about cost savings

2008

Robotics and Energy Cost Reduction
by Bennett Brumson , Contributing Editor
Robotic Industries Association
Posted 08/02/2006
http://www.robotics.org/content-detail.cfm/Industrial-Robotics-Featured-Articles/Robotics-and-Energy-Cost-Reduction/content_id/1047

Robotic systems employed in decontamination and decommissioning (D&D) applications offer potential benefits in terms of decreased personnel radiation exposure and decreased personnel costs. Robotic systems seem particularly suited to the repetitive nature of the gaseous diffusion plant (GDP) process building designs.
Google Search Link for Robots Cost Reduction


Updated 5 August 2017, 30 Jan 2014

Manufacturing Cost Policy Deployment (MCPD) and Methods Design Concept (MDC) 2017 IE Book Information


Manufacturing Cost Policy Deployment (MCPD) and Methods Design Concept (MDC): The Path to Competitiveness

Alin Posteuca, Shigeyasu Sakamoto
CRC Press, March 2017,  434 pages

Increasing profitability through increasing productivity is a fundamental task of the management teams of any production company along with introducing better and new products and earning more revenue and profits.

The MCPD system is developed by Alin Posteuca, is a manufacturing cost management policy aimed at continuous cost improvement through a systemic and systematic approach to improving productivity. The MCPD is a methodology that improves the production flow driven by the need for Manufacturing Cost Improvement (MCI) for both existing and future products through setting targets and means to continuously improve production process productivity for each product family cost.

The MDC, developed by Shigeyasu Sakamoto, designs the effective manufacturing methods using a tool of engineering steps identifying ideas for increasing productivity called KAIZENSHIRO (improvable value as a target). The MDC results on production methods lead to effectiveness of work measurement for performance (P) and to knowledge and improvement of production control and planning as utilization (U), in order to achieve target costs.

The combination of MCPD and MDC methodologies can provide a unique approach for the managers who are seeking new ways for increasing productivity and profitability to increase the competitive level of their manufacturing company.

https://books.google.co.in/books?id=r0WEDgAAQBAJ


Productivity Science - Research Project - Causal Explanation for Productivity



Suggestions are Invited

Please help in making the research project effective and useful.

Suggestions are invited for modifying the research proposal to make the research project more effective.

Suggestions are also invited for inclusion of papers in each topic. What are the seminal papers in each topic? If you authored or published any paper having causal explanation of productivity in any of the subtopics, please inform through email to nkvss at nitie dot ac dot in for inclusion in the bibliography and literature review.


Project started on 3 August 2017


The research project is exploring the research conducted so far in the industrial engineering field to identify research papers and theses (dissertations) that developed or tested causal explanation theories, propositions or hypotheses and consolidate them into a framework. The research is furthering the principles of industrial engineering proposed by Prof. K.V.S.S. Narayana Rao (Part of the Proceedings of IISE 2017 Annual Conference at Pittsburgh)


______________________


______________________

The functions of industrial engineering

______________________


Research in Industrial Engineering can be related to productivity science, productivity engineering or productivity management. The basic research in industrial engineering has to aim of creating productivity science. The science in turn is converted into productivity engineering or productivity management. Productivity engineering is using technical knowledge to redesign products and processes. Productivity management is redesign of managerial processes to enhance productivity and planning and execution of productivity improvement strategies, plans, programs and projects.
______________________


Organization of Productivity Science Theory


1. Productivity of Systems

2. Productivity of Systems - Global, National, Sectoral, Industry, Regional and Firm Levels.

3. Productivity of Resources - Machines and Equipment ( Production machines, Transport equipment, Material Handling equipment, Inspection equipment, Computing facilities, etc. ), Material, Energy, Manpower (Managers, supervisors, operators, knowledge workers), Land, Buildings, Utilities (Water, Compressed air etc.)

4. Productivity of Engineering Processes - Production, Inspection, Material handling, Maintenance, Design, Research and Development, Information processing,

5. Productivity of Different Engineering Branches-Related Technologies


Mechanical engineering


- Automobile - Development, Design, Production, and Servicing

- Machine Tools

- Boilers

- Robotics

- 3D Printers

Civil engineering


- Construction of Buildings

- Construction of Dams

- Construction of Roads

Metallurgical engineering

Mining engineering

Electrical engineering

- Generation of Power

- Distribution of Power

Electronics engineering

Communications engineering

Software engineering


- Data Analytics and Productivity
- IoT and Productivity
- Programmer productivity
- Data Center Productivity

Biotech Engineering

6. Productivity of Non-engineering Processes


Hospital Productivity

7. Productivity Science - Theories from Other Disciplines


Economics

Management

Organizational Behavior

Psychology

Sociology


In each area, seminal papers that discovered causal variables that affect productivity will be identified and the subsequent publications that extended the area will be listed. Any literature survey published on the issue will be specially highlighted. An attempt will be made to summarize and present the status of the theory on the area.

Suggestions are Invited

Please help in making the research project effective and useful.

Suggestions are invited for modifying the research proposal to make the research project more effective.

Suggestions are also invited for inclusion of papers in each topic. What are the seminal papers in each topic?

Project started on 3 August 2017


Research Papers and Articles Collected So Far

The articles collected so far are listed in the individual blog posts.

Organization of Productivity Science Theory


1. Productivity of Systems

General - System Level Productivity Science

2. Productivity of Systems - Global, National, Sectoral, Industry, Regional and Firm Levels.

3. Productivity of Resources - Machines and Equipment ( Production machines, Transport equipment, Material Handling equipment, Inspection equipment, Computing facilities, etc. ), Material, Energy, Manpower (Managers, supervisors, operators, knowledge workers), Land, Buildings, Utilities (Water, Compressed air etc.)

4. Productivity of Engineering Processes - Production, Inspection, Material handling, Maintenance, Design, Research and Development, Information processing,

5. Productivity of Different Engineering Branches-Related Technologies


Mechanical engineering


- Automobile - Development, Design, Production, and Servicing

- Machine Tools

- Boilers

- Robotics
Robots and Cost Reduction - Price and Cost Reduction of Robots

- 3D Printers
3D Printing - Additive Manufacturing - Productivity Science and Engineering

Civil engineering


- Construction of Buildings

- Construction of Dams

- Construction of Roads

Metallurgical engineering

Mining engineering

Electrical engineering

- Generation of Power

- Distribution of Power

Electronics engineering

Communications engineering

Software engineering


- Data Analytics and Productivity
- IoT and Productivity
- Programmer productivity
- Data Center Productivity

Biotech Engineering

6. Productivity of Non-engineering Processes


Hospital Productivity

7. Productivity Science - Theories from Other Disciplines


Economics

Management

Organizational Behavior

Psychology

Sociology

Wednesday, August 2, 2017

Industrial Engineering - Articles and Books (Free Download)

Books

Books by Pioneers

 ___________________________________________________________________

Books Authored by F.W. Taylor 

Principles of Scientific Management
Shop Management

Books Authored by Frank Gilbreth

Motion study : a method for increasing the efficiency of the workman (1911)
Download from
http://www.archive.org/details/motionstudymetho00gilbrich
Fatigue Study, the Elimination of Humanity's Greatest Unnecessary Waste: (1916)
Download from
http://www.archive.org/details/fatiguestudyeli00gilbgoog

Books Authored by Harrington Emerson

The Twelve Principles of Efficiency (1912)
Efficiency as a Basis for Operation and Wages



Principles of industrial engineering (1911)
Going, Charles Buxton,
First book with industrial engineering in the title
http://www.archive.org/details/principlesofindu00goinrich
______________________________________________________________________

Other Books

Operation Analysis by Maynard, 1939
Presgrave, R., The Dynamics of Time Study, McGraw-Hill, New York, 1945
http://babel.hathitrust.org/cgi/pt?id=mdp.39015064385779
Human and Industrial Effiency

An introduction to the psychological problems of industry ([1921])
Watts, Frank
Has good discussion of Gilbreth's methodology ad Taylor's methodology
http://www.archive.org/details/introductiontops00wattiala

The new industrial engineering : information technology and business process redesign

More Books 

Online Books On Industrial Engineering and Related Subjects

Articles and Research Papers


Knols

Introduction to Industrial Engineering

The Component Areas of Industrial Engineering

   

Human Effort Engineering - Methods, Techniques and Related Issues 

Systems Efficiency Engineering - Methods, Techniques and Related Issues 

Systems Design, Installation and Improvement Management

Methods, Techniques and Related Issues 

Pioneers and Expert Practitioners of Industrial Engineering

Organizing Industrial Engineering Department

Industrial Engineering and Other Departments and Disciplines

Industrial Engineering Programs

Articles, Books, Bulletin Boards, Course Pages



Industrial Engineering Optimization

Extremal Methods and Systems Analysis: An International Symposium on the Occasion of Professor Abraham Charnes’ Sixtieth Birthday Austin, Texas, September 13 – 15, 1977
A. V. Fiacco, K. O. Kortanek
Springer Science & Business Media,  550 pages
https://books.google.co.in/books?id=P9HzCAAAQBAJ

Articles

Introduction
Human Effort Engineering
Work Measurement in Skilled Labor Environments, Tom Best
History - IE
Scientific Management and Industrial Engineering at Dupont
Future of Industrial Engineering
Future of Industrial Engineering is in our Hands
Louis Martin-Vega, Industrial Engineering, December 2008
http://www.entrepreneur.com/tradejournals/article/190946367.html


IIT Roorkee, NPTEL Course Material

Part 1
>
Lecture 1
>
Lecture 2
>
Lecture 3
>
Lecture 4
>
Lecture 5
>
Lecture 6
>
Lecture 7
>
Lecture 8
>
Lecture 9
>
Lecture 10
>
Lecture 11
Part 2
Quality and Related Concepts
>
Lecture 1
>
Lecture 2
>
Lecture 3
>
Lecture 4&5
>
Lecture 6
>
Lecture 7&8
>
Lecture 9
Facility Design
>
Lecture 1
>
Lecture 2
>
Lecture 3
>
Lecture 4
>
Lecture 5
Material Handling
>
Lecture 1
>
Lecture 2
Reliability
>
Lecture 1
>
Lecture 2
 > Lecture 3
Part 3
CPM/PERT
>
Lecture 1
>
Lecture 2
Forcasting
>
Lecture 1
>
Lecture 2
PPC
>
Lecture 1
MRP
>
Lecture 1
Inventry
>
Lecture 1
>
Lecture 2
PDD
>
Lecture 1
>
Lecture 2


Blog Posts

Industrial Engineering, a continuing productivity influence
Ford links good ergonomic job design to improved quality

Working Papers

Systems Design Issues

Models for Strategic Analysis of Forest Management and the Forest Products Supply Chain, 2007