Sunday, December 31, 2023

Health Care - Hospital Industrial Engineering - Online Book

New Collection 31.12.2023

Introduction to Healthcare for Industrial Engineers
https://slideplayer.com/slide/5911315/

How can you improve healthcare delivery systems with industrial engineering?
https://www.linkedin.com/advice/3/how-can-you-improve-healthcare-delivery


So You Want to be an Industrial Engineer in Healthcare? 
By: Ali Hobbs
https://www.iise.org/details.aspx?id=50195%20

INDUSTRIAL ENGINEERING IN HEALTHCARE
Speaker Dr. Maryam Zaghian, MD Anderson Cancer Center Office of Performance Improvement
https://www.ie.uh.edu/research/seminar/202303/industrial-engineering-healthcare


How Industrial Engineers Will Save Health Care
December 7, 2012
About the Author: Shayna Pepin
https://illumin.usc.edu/how-industrial-engineers-will-save-health-care/



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Old Collection 16.10.2012

Industrial Engineering and Healthcare
Koelling, C Patrick, PhD; Schwandt, Michael. IIE Annual Conference. Proceedings (2006): 1-6.



Healthcare Systems Engineering - Context and Techniques
Wu, Bin; Klein, Cerry. IIE Annual Conference. Proceedings (2006): 1-6.


Data Envelopment Estimates for the Most Efficient National Healthcare Systems Given Uncertain Proportional Rate Inputs
Ceyhan, Mehmet E; Benneyan, James C. IIE Annual Conference. Proceedings (2008): 1760-1765.




Human Effort Engineering

Training


Training in Health Care: The Benefits of Context and Emergency Simulation on Patient Handling
Resnick, Marc L; Sanchez, Roderick. IIE Annual Conference. Proceedings (2008): 46-51.


System Efficiency Engineering

Methods Efficiency Engineerng
Process Analysis, Operation Analysis, Methods Study


Frank Gilbreth and health care delivery method study driven learning
Towill, Denis R. International Journal of Health Care Quality Assurance22. 4 (2009): 417-440.


Engineering Economics


The Health Care Economics of Automating Health Care Systems
Jones, Erick C; Thummalapalli, Rama. IIE Annual Conference. Proceedings (2010): 1-6.


Application of Statistics


A survey on statistical methods for health care fraud detection
Li, Jing; Huang, Kuei-ying; Jin, Jionghua; Shi, Jianjun. Health Care Management Science11. 3 (Sep 2008): 275-87.


Stratified random sampling for estimating billing accuracy in health care systems
Buddhakulsomsiri, Jirachai; Parthanadee, Parthana. Health Care Management Science11. 1(Mar 2008): 41-54.



Stratification and Clustering Methods for Billing Accuracy in Healthcare Systems
Parthanadee, Parthana; Buddhakulsomsiri, Jirachai; Kachhal, Swatantra. IIE Annual Conference. Proceedings (2006): 1-6.



OR and Optimization


Modeling and Optimization of Health Care processes
Ramudhin, Amar; Chan, Eric; Benziane, Riadh; Mokadem, Abdelkader. IIE Annual Conference. Proceedings (2006): 1-6.





Improving Emergency Department Physician Management via Computer Simulation
Xu, Samuel; Rogers, Paul; Rohleder, Thomas R; Cooke, David L. IIE Annual Conference. Proceedings (2008): 834-839.


Real Life Issues in Modeling Health Care Capacity (Presentation)
Goto, Jason; Wong, Simon. IIE Annual Conference. Proceedings (2008): 1-69.


Techniques in Modeling Healthcare Operation Data from Hospitals to Improve Scheduling: a Review and Assessment
Rinder, Maria M; Weckman, Gary. IIE Annual Conference. Proceedings (2010): 1-6.


Reducing patient wait times and improving resource utilization at British Columbia Cancer Agency's ambulatory care unit through simulation
Santibáñez, Pablo; Chow, Vincent S; French, John; Puterman, Martin L; Tyldesley, Scott. Health Care Management Science12. 4 (Dec 2009): 392-407.




JIT and Lean in Health Care


Measuring lean initiatives in health care services: issues and findings
Kollberg, Beata; Dahlgaard, Jens J; Per-Olaf Brehmer. International Journal of Productivity and Performance Management56. 1 (2007): 7-24.



A Discussion and Model of Risk in Hospital Evacuation Planning
Becker, Lindsay; Brenes, Jaclyn; Hatcher, Michelle; Taaffe, Kevin. IIE Annual Conference. Proceedings (2007): 43-47.


A Test of the Design Rules in Health Care
Ghosh, Manimay; Sobek, Durward K, II. IIE Annual Conference. Proceedings (2006): 1-6.


Integrating Systems Engineering Technologies to Drive Health Systems Performance Improvement
Koelling, C Patrick; Schwandt, Michael. IIE Annual Conference. Proceedings (2007): 487-492.


31.12.2023
16.oct 2012
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Friday, December 29, 2023

Machine Shop Industrial Engineering

Do it. It is Real Engineering. Industrial Engineering is Engineering Primarily.

Find 5 new engineering developments every day in elements related to facilities, products and processes in your organization and assess their use for industrial engineering. 

Best Practices in Industrial Engineering 

https://nraoiekc.blogspot.com/2022/06/do-it-it-is-real-engineering-industrial.html


Machine Shop Product Industrial Engineering

Value engineering

DFMA for Machining


Machine Shop Facilities and Resources Industrial Engineering


Review of Selection of Equipment - Replacement Analysis

Improvement of Machines and Addition of Accessories

Layout Analysis

5S Analysis -  Every item in a planned and designated place. Highly visible work place reducing search time for any item.

Workstation Design

Selection of Machinists and Other Operators

Training

OEE based maintenance - TPM


Machine Shop Processes Industrial Engineering

Process charting for parts made - Operation Process Chart - Flow Process Chart - Operation Information Sheets

Periodic process chart analysis - Operation Analysis

Determination of Optimal Cutting Parameters.

Management of Productivity Improvement by Shop Operations Team


Regarding machine oriented work improvement.  

OEE accepted as a metric and now we are going ahead with a pilot area of three horizontal milling machines.

Once we get a good baseline of where all machines stand, I aim to run a DOE to have optimal process parameters.

Focusing on production operation,  Would you recommend any more specific strategies/tools to deal with the machine oriented manufacturing?

Message from https://www.linkedin.com/in/abhiramboralkar/



Machine Shop Industrial Engineering - An Agenda for 2022 by DR. SHAHRUKH A. IRANI, LEAN & FLEXIBLE LLC


Check part routings - correct errors. Revise misfit operations.

Identify the additional transport due to current layout.

Make small changes to the layout.

Make radical changes to the layout.

Purchase FMC (flexible manufacturing cell) to do lightout manufacturing in the night shift.

Ensure JIT Material Handling and Logistics for cells

Implement phased automation

Rationalize product mix and reject unprofitable parts.

Make efforts to expand parts that are profitable and done in cells in flow method.


You can download the detailed noted from this LinkedIn post.

https://www.linkedin.com/posts/shahrukh-irani-8b25a55_how-to-simplify-the-shop-floor-chaos-in-any-activity-6967670373978947585-JEQC   



Industrial Engineering Strategy for Machine Shop.

Strategic decisions related to industrial engineering function?


1. What is your productivity/Efficiency Improvement - Cost Reduction goal?

2. Are you planning to realize experience curve effect benefits?

3. How much of the cost reduction - productivity improvement should come from specialist industrial engineers and other engineers and managers?

4. What will be the ratio of industrial engineers to other engineers and managers?

5. What bottlenecks or limiting factors have you identified in the machine shop?

6. What techniques are going to receive special emphasis?

7. What is your training plan for specialist industrial engineers and other engineers and managers?

8. What is the top management attention to industrial engineering - productivity improvement - cost reduction activity? - Planning and Review Meetings

9. What is the research and development budget for IE activity?

10. What is the total budget for productivity improvement? What is the budget for productivity projects to be initiated by industrial engineering department? What is the budget for productivity projects to be initiated by operating departments?

https://nraoiekc.blogspot.com/2014/11/industrial-engineering-strategy.html


Machine Shop Facilities and Resources Industrial Engineering


Review of Selection of Equipment

Improvement of Machines and Addition of Accessories

Replacement Analysis

Layout Analysis

5S Analysis

Workstation Design

Selection of Machinists and Other Operators

Training


Machine Shop Processes Industrial Engineering

Process charting for parts made

Periodic process chart analysis

Management of Productivity Improvement by Shop Operations Team


Machine Shop Products Industrial Engineering

Value engineering

DFMA



Productivity Science

Productivity Engineering

Productivity Management


Knowledge Base and Lessons for Machine Shop Industrial Engineering - Productivity Improvement and Cost Reduction 

https://nraoiekc.blogspot.com/2021/05/knowledge-base-for-machine-shop.html

How to Make a Machine Shop Lean - Dr. Shahrukh Irani - Chapter Summary

Published 8/1/2018 

10 Lean Manufacturing Ideas for Machine Shops

In addition to the right mix of traditional strategies, a new lean manufacturing toolkit can make high-mix, low-volume machining faster, more predictable and less expensive.

DR. SHAHRUKH A. IRANI, LEAN & FLEXIBLE LLC

https://www.mmsonline.com/articles/10-lean-manufacturing-ideas-for-machine-shops




Ud. 29.12.2023, 25.8.022

Pub. 1.7.2022





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Machine Shop Process Industrial Engineering

Taylor's Industrial Engineering - Machine Shop Process Industrial Engineering.

Yes Taylor's Industrial Engineering  is first machine effort improvement to increase productivity and then human effort engineering to reduce human effort involved in operating machines. Of course, in pure human effort tasks, there is no machine. In such tasks, industrial engineers have no special advantage in design and improvement tasks. Of course, special techniques and methods were developed in scientific management and industrial engineering areas to study human effort. But still in pure human effort tasks, the engineering expertise is not required. 

What is Industrial Engineering?

Industrial engineering is system efficiency engineering. It is done on products, facilities and processes.

Its primary tasks in the area of processes are machine effort industrial engineering  and human effort industrial engineering. - Narayana Rao.

Industrial Engineering:
Activity related to developing the most efficient ways to utilize people, assets, materials, information, and energy to make a product or service. - Novartis
https://nraoiekc.blogspot.com/2020/04/industrial-engineering-novartis-way.html


Industrial engineering is  Shop Floor (Gemba) based (現場)  continuous engineering of products and processes to increase productivity/efficiency/cost reduction
80 - 20 Rule in Industrial Engineering - 80% Engineering changes - 20% Change in Human Motions and Movements
https://nraoiekc.blogspot.com/2019/11/80-20-rule-in-industrial-engineering-80.html

EBook Free Download.  MODERN INDUSTRIAL ENGINEERING. 7150+ DOWNLOADS so far. 
PRODUCT INDUSTRIAL ENGINEERING (Value) - FACILITIES INDUSTRIAL ENGINEERING (Lean)  - PROCESS INDUSTRIAL ENGINEERING (Minimizing Effort - Machine - Man). Industrial engineers manage cost reduction and productivity improvement and contribute directly to profit increase.


Knowledge for Machine Shop Industrial Engineering

Machine Shop Technology and Process Cost Reduction News

2021 - 2020 - 2019 - 2018 - 2017 - 2016 - 2015 - Up to 2014

Productivity Improvement in Machine Shop - F.W. Taylor  - Basic Theory and Foundation (1895 to 1912)

DFMA - Design for Machining - Summary Notes

Principles of Industrial Engineering - Taylor - Narayana Rao - IISE Annual Conference 2017

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Focus Areas of Industrial Engineering - Brief Explanation


Productivity Science: Science developed for each element of machine operation and each element of human tasks in industry.
Productivity Science - Determinants of Productivity

Product Industrial Engineering: Redesign of products to reduce cost and increase value keeping the quality intact.
Product Industrial Engineering


Process Industrial Engineering: Redesign of processes to reduce cost and increase value keeping the quality intact.
Process Industrial Engineering

Industrial Engineering Optimization: Optimizing industrial engineering solutions created in Product Industrial Engineering and Process Industrial Engineering.
Operations Research - An Efficiency Improvement Tool for Industrial Engineers

Industrial Engineering Statistics: Using statistical tools like data description, sampling and design of experiments in industrial engineering activity.
Statistics and Industrial Engineering

Industrial Engineering Economics: Economic analysis of industrial engineering projects.
Engineering Economics is an Efficiency Improvement Tool for Industrial Engineers


Human Effort Industrial Engineering: Redesign of products and processes to increase satisfaction and reduce discomfort and other negative consequence to operators.
Motion Study - Human Effort Industrial Engineering

Productivity Measurement: Various measurements done by industrial engineers in industrial setting to collect data, analyze data and use the insights in redesign: Product Industrial Engineering and Process Industrial Engineering.
Industrial Engineering Data and Measurements

Productivity Management: Management undertaken by industrial engineers to implement Product Industrial Engineering and Process Industrial Engineering. Management processes industrial engineering is also part of productivity management.
Productivity Management

Applied Industrial Engineering: Application of industrial engineering in new technologies, existing technologies, engineering business and industrial processes and other areas.
Applied Industrial Engineering - Process Steps

How many Industrial Engineers can a Company Employ for Cost Reduction?

For $100 million cost, there can be one MS IE and 6 BSIEs.
https://nraoiekc.blogspot.com/2020/03/value-creation-model-for-industrial.html

Industrial Engineering - Lean Manufacturing - Parent - Child Relationship

Machine Shop Process Industrial Engineering 

Cost Reduction - Productivity Improvement



The first major research work in the area machine shop process industrial engineering i.e., productivity improvement was done by F.W. Taylor. A series of experiments,  theory development and application were done over a period of 26 years. Industrial engineers have to compulsorily read the full book or paper to understand the scope machine productivity improvement component of industrial engineering. No doubt this research work is limited to work on lathe. But that provides the framework for working on other machines and related processes.

Read the paper in the ASME Proceedings
ON THE ART OF CUTTING METALS
https://babel.hathitrust.org/cgi/pt?id=mdp.39076000032131&view=1up&seq=61&size=125


Machine Shop Product Industrial Engineering

DFMA - Design for Machining - Summary Notes

Focus Areas of Industrial Engineering in Machine Shop Process Industrial Engineering 


All the focus areas of industrial engineering can be utilized in the machine shop to improve operations and processes continuously and achieve cost reduction. Here are the illustrations for each relevant focus area.


Process Industrial Engineering - Process Alternatives


Cutting tool features and machining productivity


An improperly designed tool may wear or chip rapidly or unpredictably, reducing productivity, increasing costs, and producing parts of deteriorating quality. Tooling thus has a major influence on the productivity and economics of a process.

Cutting-tool material and design have a strong impact on machining performance. Properly designed tools produce parts of consistent quality at higher cutting speeds and feeds and also have long and predictable useful lives. An improperly designed tool may wear quickly or chip rapidly or unpredictably, reducing productivity, increasing costs, and producing parts of deteriorating quality. Tooling has a major influence on the productivity and economics of a process. Therefore it is important to consider all material options and tooling geometries for a given application with associated range of speeds and feeds and their typical failure modes. In high-volume applications, perishable tooling costs are typically 3% of the component cost.  Using higher cost tool capable of running at higher material removal rates (MRRs) normally is profitable  since a 20% increase in the MRR could reduce the total cost per component by 15%. Modifying tooling to increase tool life can also be attempted as 50% increase in tool life reduces the total cost per component by 1%–2%.

For nonferrous work materials, WC tools will exhibit 2–3 times the productivity and 10 times the life of HSS tools. In steels, they give 2 times the productivity and 5 times the life.

Sintered Tungsten Carbide (WC)

Basic guidelines for selecting carbide grades are (1) use the lowest Co content and finest grain
size, provided edge chipping and tool breakage do not occur; (2) use straight WC grades when
abrasive edge wear is of concern; (3) use TiC grades to prevent crater wear and/or both crater and
abrasive wear; (4) use TaC grades for heavy cuts in steels.

Even though the range of rake angles is generally −5° to +15°, higher positive angles are slowly being used to improve productivity.

Multipoint boring bars are often used to improve stability and to increase productivity in high volume applications.

Rotary milling cutters can be used in some applications to improve productivity.

Significant improvements in productivity have resulted from the acceptance of solid carbide drills. Compared to HSS drills, carbide drills permit an increase in productivity by a factor of 2–10, and/or increase in hole quality. Solid carbide drills are especially well suited for high throughput precision hole manufacturing.

Internal coolant is more effective; this method cools and lubricates the cutting edge and reduces thermal shock in addition to removing chips, and therefore often results in improved tool life and productivity.

The process industrial engineering illustrations use cutting tool substitution as the way to increase productivity and reduce cost.


 Plataine’s ‘AI and IIoT’ in Aerospace & Automotive composites manufacturing for Productivity Improvement and Waste Elimination
October 25, 2021

The key role of ‘AI and IIoT’ in Aerospace & Automotive composites manufacturing

Siemens is integrating Plataine’s technology into their Manufacturing Operations Management (MOM) solution Opcenter. Plataine has  deep domain knowledge in the field of aerospace composites and IIoT solution.  AI-based algorithms analyse the data and provide smart insights and predictions to the factory floor operator to make optimized, data driven decisions  across factories. The MOM solution consolidates all production processes to deliver another level of visibility on top of an MES.  The result is improved quality, the ability to perform advanced planning, and better direction of product design efforts; as well as improved efficiency, flexibility, and time-to-market. Plataine brings  new range of capabilities to MOM in the area of composites processing.

Real-time monitoring of raw materials
Combining AI-based IIoT technology with RFID tags allows all composite raw material rolls to be tracked in real-time as soon as they enter the factory – including monitoring of material shelf-life. AI-based algorithms proactively apply the intelligence to analyze the historical manufacturing data and offer predictions related to late work orders, material expiration and suggest actions to prevent these problems. If there is an unexpected production delay causing the ETL (expiration time left) to run low, Digital Assistants alert employees to the best course of action – which is likely to be either to use another raw material with a longer ETL. Also it alerts operators to focus on expediting  finished parts  into the autoclave.

Optimized cutting and kitting processes

With the Plataine-Siemens solution, ready-to-cut production plans are automatically created. The fully CAD-integrated AI software achieves optimal material utilization by taking all variables – such as dynamic customer orders – into account. To save material, the AI-based software fits as many plies into each cut plan as possible, while advanced optimization algorithms ensure optimal plans even with mixed work orders, which results in higher material yield. 

IE Measurements


Industrial engineers have to take measurements of machining operations in the areas of time, cost and productivity at the start of the engineering study as well as at the end of the industrial engineering study. Measurements are taken at the start of the study as through literature review or secondary sources, alternatives that offer less time, or less cost or more productivity can be selected. The measurements taken at the beginning of the study are also important for guiding thinking in brainstorming exercises that are done after the group members do focused study of the existing knowledge. Measurements at the end of the study validate the improvements made and provide the standards for further operations.

Time Measurement also termed work measurement
Cost Measurement (Cost Accounting - Cost Estimating)
Productivity Measurement (Output for each input of various resources, as well as combinations resources)


Process Industrial Engineering - Process Alternatives and Economic Analysis of IE Proposed Alternatives


The possible profitable alternatives to current practice have to be developed based on the knowledge of available tools and their applications,  understanding of the requirements of the job being improved and creativity. Creativity is essential in industrial engineering problem solving.

The alternatives have to be subjected to engineering economic analysis for selection as the possible solution.

Up to 60% cycle time reductions on turning using MAXX Machining
4 May 2020
https://www.youtube.com/watch?v=JgURz335Jao
Channel: https://www.youtube.com/channel/UC09R-RDOwz88FqD--3YWmew (MTD CNC)
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Illustration: Economic analysis of PCD tool in cutting composite material


Carbon fiber reinforced plastic materials are about 70% lighter than steel and about 40% lighter than aluminum, while costing only about 20% more.

More examples of successful machining time reduction through cutting tool alternatives
Economic - Cost Analysis - Cutting Tool Alternatives


Metal Working Fluids - Cutting Fluids - Alternatives

Minimum Quantity Lubrication (MQL) in Automotive Powertrain Machining in Ford

The primary benefits from MQL include cost reduction that includes reduction in energy consumption, improvement in environment, and more effective chip recycling.

Ford began investigating alternatives to conventional flood coolant machining technology for aluminum materials in the 1990s through a collaborative project seeking to completely eliminate coolants with an aim towards completely dry machining of aluminum. Many machining operations for ferrous components were already dry.  The project was carried out through extensive laboratory trials and a series of small-scale production pilots in early 2000s

Ford began applying MQL to aluminum transmission components in 2005, and by 2008 had over 200 MQL machining centers in operation machining aluminum transmission cases, torque converter housings, and valve bodies at two plants in North America. MQL machining became Ford’s current standard machining method for these components, and is being implemented in new high-volume machining lines globally. Ford began machining aluminum engine heads and cast iron engine blocks  in 2011. MQL is now the primarily standard method for machining cast iron engine blocks and aluminum engine blocks and heads. For some specialized operations still wet machining is used . MQL machining modules are being installed in plants in new locations like Brazil and China.

Ford is making effort to extend MQL machining to additional components like CGI engine block machining, thermally sprayed engine bore machining, and aluminum deep hole drilling. There are technical challenges and the research community and engineering community are involved in finding solutions and extend MQL to new areas of application.

Source:
Minimum Quantity Lubrication (MQL) in Automotive Powertrain Machining
Bruce L. Tai, David A. Stephenson, Richard J. Furness, Albert J. Shih
6th CIRP International Conference on High Performance Cutting, HPC2014
Procedia CIRP 14 ( 2014 ) 523 – 528
doi: 10.1016/j.procir.2014.03.044

2019

Cryogenic Machining Technology Used for Cost Reduction


The thru-tool cryogenic machining technology was further developed 5ME LLC under  license and it  markets it as 5ME® Cryogenic Machining Technology. The system can be used to optimize the performance, sustainability, and part quality of steel, aluminium, and other alloys as well as composite materials. Lockheed Martin is using the cryogenic machining technology to cut titanium parts for the F-35 Joint Strike Fighter, significantly increasing efficiency and lowering costs. Lockheed's Value Engineering team estimates the cost savings/avoidance as over $500 million for the program.
(Cryogenic machining is also a part of Minimum Quantity Lubrication Method)


Machine Shop Industrial Engineering - Operation Process Chart and Flow Process Chart Operations Analysis and Improvement


Material Processing

CNC Working Process | Watch Case making with on Brother Machine CNC | Stainless steel
CAD/CAM SOLUTION, 10 Feb 2021
Brother Machine CNC SPEEDIO S300X2
Material : SUS304/Stainless Steel
https://www.youtube.com/watch?v=AjTcWxl_BLA

Process Planning Introduction
Fredumacation, 18 Oct 2020
https://www.youtube.com/watch?v=sfF1rojlTI0

Jigs and Fixtures: 6 Ways to Improve Production Efficiency with 3D Printing
13 May 2021
https://amfg.ai/2021/05/13/jigs-and-fixtures-6-ways-to-improve-production-efficiency-with-3d-printing/


6 Computer Numerical Control (CNC) Machining Trends for 2021
By Larry Alton

Production and process optimization in CNC manufacturing
https://new.siemens.com/global/en/products/automation/systems/cnc-sinumerik/digitalization/manufacturing.html

Machine shop tool management (May be we can put in warehousing or storage or facilities IE)
https://www.steckermachine.com/blog/managing-machine-shop-tools

Inspection

Renishaw probing increases productivity for machine shop ‘down under’
2 DECEMBER 2021 
https://www.pesmedia.com/renishaw-probing-17112021
https://www.heidenhain.us/product/machine-controls-and-touch-probes/

Automotive Supplier Scans Machined Connecting Rods With Diamond Styli for Low Tool Wear.


Silicon nitride stylus tips of micrometers used for scanning were wearing down at a rate of up to one per micrometer per day .
 Hearing about new styli with a diamond coating from the field staff at ZEISS Industrial Metrology piqued Pichler’s interest and ordered a loaner stylus – initially the more expensive, solid-diamond version – for one of the two ZEISS PRISMO systems used for the final inspection of connecting rods.
After more than a year, Pichler reports: “We haven’t noticed any wear thus far.”  “switching to the diamond-coated and solid-diamond styli has definitely paid off.”
December 17, 2021
https://metrology.news/automotive-supplier-scans-parts-with-diamond-styli/

9/1/2021 
Digital Part Inspection Software. 
Chick Machine overhauled its decades-old inspection process and landed new clients that have propelled the growth of the company.
https://www.mmsonline.com/articles/digital-part-inspection-software-creates-new-business-opportunities-

Material Handling, Transport and Layout



Why NOW is the Time for Machine Shops to Automate
READY Robotics, 16 Aug 2021
https://www.youtube.com/watch?v=fniNBfHcupE

Raw Material and Parts Storage

Temporary Delays or Delays in Flow

Machine Shop Facilities Industrial Engineering


Industry 4.0 Implementation for Small and Medium-Sized Shops
April 22, 2021
Rizzie: The complexity of Industry 4.0, or the appearance of complexity, is what keeps most people from implementing it. At Sandvik Coromant, instead of thinking of it as an Industry 4.0 problem, we call it the connected machine shop.
https://www.sme.org/technologies/articles/2021/april/industry-4.0-implementation-for-small-and-medium-sized-shops/

Digital Machine Shop Guide
https://cdn.brandfolder.io/GDDASP4K/as/xm6phpcb3hrkgpk79782f6s/LM-0011_Digital_Machine_Shop_Ebook.pdf

Total Productive Maintenance (TPM) Implementation in a Machine Shop: A Case Study
December 2012Procedia Engineering 51(7)
DOI:10.1016/j.proeng.2013.01.084
Conference: Chemical, Civil and Mechanical Engineering Tracks of 3rd Nirma University International Conference on Engineering (NUiCONE2012)Volume: Volume 51, 2013, Pages 592–599
https://www.researchgate.net/publication/236594199_Total_Productive_Maintenance_TPM_Implementation_in_a_Machine_Shop_A_Case_Study

Automated Machine Tool Cell
6/18/2021 | 
Automated production line, including its automated storage and retreival system called the Mazatec Smart Manufacturing System, or SMS. Taken together, the system represents an integrated manufacturing cell designed to perform unmanned machining through the use of horizontal machining centers and multitasking machines, along with the material handling technology of Murata Machinery. Murata is best known for its expansive capabilities in material handling, and — in the case of the SMS — its vertically orientated, modular, six-level stocker-type system that includes pallets, automated load stations and high-speed stacker crane. 

AUTOMATION
10/7/2021 
Buying Robot on Experimental Basis and Using it Profitably for a Machine Tool Tending Job. 

Connected Machine Shop - Part 2

IEOR Optimization - IE Statistics Optimization - Six Sigma Method

IEOR - Optimization in Machining Processes


1973
MIT Working Paper
AUTOMATED PLANNING AND OPTIMIZATION OF MACHINING PROCESSES: A SYSTEMS APPROACH
by
Krishna Challa and P. Bruce Berra
November 1973 



Automated planning and optimization of machining processes: A systems approach
Krishna Challa and P. Bruce Berra
Computers & Industrial Engineering
Volume 1, Issue 1, 1976, Pages 35-46

More papers given in: Optimization of Machining - Bibliography


IE Statistics Optimization - Six Sigma Method


Taguchi-Based Six Sigma Approach to Optimize Surface Roughness for Milling Processes
Authors: Joseph C. Chen, Sky Chou
2007

This illustration focuses on using Six Sigma methodologies to improve the surface finish of a manufactured part produced by the CNC milling machine and reduce defects produced by the operation. Milling of  aluminum is operation. The Taguchi-based six sigma approach was applied to identify the optimized processing parameters that lead to reduced variability in surface finish specified by the customer. A L9 orthogonal array was applied in the Taguchi experimental design,  The controllable factors are feed rate, depth of cut, and spindle speed,  The confirmation run with the optimal parameters determined in the study confirmed that the new parameter settings are correct. The new settings also improved the process capability index. The  study confirms that  the Taguchi–based six sigma approach can be efficiently used to reduce defects by minimizing variation of the operation and improve the process capability index of the CNC milling process.
https://publications.waset.org/10007983/taguchi-based-six-sigma-approach-to-optimize-surface-roughness-for-milling-processes

More Case Studies on Six Sigma in Machining


Human Effort Engineering in Machine Shop


Ergonomics Applied to CNC Machining

MAY 5, 2014

The science of ergonomics involves designing and arranging things so that people can use them as efficiently and easily as possible. When ergonomics is applied to CNC machining the primary focus is on improving productivity and safeguarding the machine operators.

A few examples of how Gosiger Automation builds ergonomics into its systems.

Loading and unloading heavy parts.

See a video of a Gosiger Automation designed cell that uses a Fanuc r-2000 iB robot with a vision system loading and unloading a 100+ pound part delivered to it on an automatic conveyor.

Eliminating repetitive motion.
Even smaller, lighter parts present ergonomic problems best overcome with a robot. A machine operator who is constantly opening and closing the machine tool door, lifting and placing the part into position, then removing the part and loading another is performing repetitive motions that can take their toll on the person’s joints, back and extremities

Seen in a video, how a family of parts can be robotically loaded and unloaded, placed in an inspection fixture, automatically checked using a Renishaw Equator and, using software to analyze the results, make tool offsets all without operator intervention.

Allowing safe access for machine tool maintenance.

 https://www.gosiger.com/news/ergonomics-robotic-automation

More on ergonomics
http://www.ilocis.org/documents/chpt29e.htm
https://webstore.ansi.org/industry/ergonomics/machine-ergonomics
http://blog.lenoxtools.com/industrial-metal-cutting/2015/11/20/machine-shops-use-ergonomics-to-increase-productivity-and-reduce-injury/


Applied Industrial Engineering in Machine Shop


Machine Tool Analytics - Analytics for Machine Tools


Turn Machine Tool  Data into Productivity - Industrial Engineering 4.0



MT Analytics offers Industry 4.0 solutions using data Analytics and a hardware Test Lab .

The MT Analytics GmbH is running a component test lab for machine tool and automotive components and provides services to their customers identifying and optimizing dynamical and geometrical problems of discrete manufacturing production systems. Beside MT Analytics GmbH provides Data Analytic Software solutions to optimize given NC Codes and to monitor the quality of parts as well as the condition of all machine tool components. Machine internal data are analyzed in real time by our algorithms that include our expert knowledge and the experience in testing, modeling and optimizing hardware.

Hardware Test Lab
The MT Analytics GmbH is running a Component Test Lab for machine tool and automotive components and provides services to their customers identifying and optimizing dynamical and geometrical problems of discrete manufacturing production systems

Data Analytics
The MT Analytics GmbH provides Data Analytic Software solutions to optimize given NC Codes and to monitor the quality of parts. Machine internal data are analyzed in real time by our algorithms that include our expert knowledge in testing, modeling and optimizing Hardware.



Make Cutting Tool Suppliers Partners in  Productivity Improvement


8/14/2009
Tooling Supplier's  Productivity Improvement Program (PIP) gives excellent benefits

Even a shop that is committed to continually optimizing processes might struggle with the time and effort required to stay abreast of the latest technology developments. One manufacturer has taken steps toward eliminating this problem by making a cutting tool manufacturer partner in in improvements.
Sandvik's Productivity Improvement Program (PIP). Through PIP, Sandvik technicians collaborate with customer personnel to optimize their manufacturing operations.
https://www.productionmachining.com/articles/tooling-supplier-expertise-lends-competitive-edge


Machine Shop Maintenance


2021

Checklist -  Top Preventive Maintenance Tips for Your CNC Machine Tools
by Hwacheon Asia - Aug 6, 2021.





Preventive Maintenance Checklist
(Schedule regular maintenance or servicing sessions, and maintain documentation of service/maintenance. Also, have a specific area for your employees to report issues.)

MECHANICAL SYSTEM
Verify machine level
VMC – verify spindle sweep
Lathe – verify turret square to spindle face
Check lubrication is reaching the spindle
Inspect rotary oil level (mill)
Inspect drive belts
Verify gearbox/motor operation
Inspect tool changer and lubricate
Inspect spindle taper condition (mill)
Inspect toolholders and grease pull studs (mill)
Verify smooth turret indexing (lathe)
 LUBRICATION SYSTEM 
Inspect filter
Inspect hoses and fittings
Check pump operation / test
Check/adjust pressure, spindle regulator
Inspect system for leaks
Change gearbox oil (lathe only)
Change hydraulic fluid and filter 
ELECTRICAL SYSTEM
Clean electrical cabinet
Check incoming voltages
Check DC bus voltage
Inspect connections and terminals
Inspect electrical ground connections
Replace or clean filter fan
Check safety locks
Check axis motors and cables
COOLANT SYSTEM
Inspect coolant hoses
Verify all pump operation
Clean coolant filters
Test and adjust coolant concentration
Inspect coolant tank for sediment
AIR & LUBRICATION SYSTEM
Inspect all lines and hoses
Verify all pump operation
Check incoming air supply
Verify lube/pump operation for axes
MECHANICAL SYSTEM:

Inspect tool holders/grease pull studs.
Inspect the rotary oil level (Mill)
ENCLOSURE/SAFETY:

Inspect safety interlock operation
Inspect windows for damage
Inspect way covers and wipers
PROBE SYSTEM:

Check the probe batteries
Check probe calibration

Monitoring the condition of the spindles: Sensemore uses Trigger device. Trigger sends the measurement order to the sensor by transmitting the 5V signals to the receiver with a code to be returned at the end of each process. Thus, it can monitor the vibrations of a CNC lathe in the grinding wheel spindle at the end of each machining and in a way that the parameters remain the same in every measurement.

Operating the grinding wheel spindle at a constant speed for a short time at the end of each machining and taking vibration measurements during this process will create a correct trend as it is within certain boundary conditions. The code added to the CNC lathe sends a 5V signal to the Sensemore Trigger device after each part is machined. Sensemore Trigger gives the measurement order by triggering the Wired with the signal it receives. The whole process is completed in as little as five seconds and analyzes are performed on the Sensemore cloud application.  

Nowadays, maintenance, and quality processes are carried out in an automated manner. . Sensemore, thanks to the portable accelerometers, application-specific hardware, and cloud-based analysis program they developed, offer easier and more reliable automated maintenance and quality control processes.

Troubleshooting CNC Breakdowns and Steps to Avoid Them
March 22, 2021

Industry 4.0 in CNC Machine Monitoring

Machine Shop Industrial Engineering - Bibliography


2019


HOW TO START A CNC SHOP: EVERYTHING YOU NEED TO KNOW
Don Sears,  Posted Mar 12, 2019



Improving machining process by College students in their project work on lathes
https://books.google.co.in/books?id=bsqDDwAAQBAJ&pg=PA329#v=onepage&q&f=false

https://www.researchgate.net/publication/330360898_Time_Optimization_Implementation_in_Conventional_Lathe_Machining_Operations


Reconfigurable Manufacturing Systems: From Design to Implementation
Lyes Benyoucef
Springer Nature, 19-Oct-2019 - Technology & Engineering - 250 pages
https://books.google.co.in/books?id=0uK3DwAAQBAJ

2018
https://www.industr.com/en/metal-working-fluid-performance-in-aluminium-high-speed-machining-2351265

2013

Questions from an Industrial Engineer in an Automotive Machine-Shop
I received the following questions from an Industrial Engineer (IE) who has recently moved from vehicle assembly to the machining of car engine parts, blocks, heads, crankshafts, etc., activities that all new to him:

Any reading material you would recommend?
Is takt based off the slowest machine or the machine in the line that makes the least parts?
Knowing cycle times and uptimes of a 30 machine line how do you calculate system uptime?
Should there be more overspeed for machines at the beginning half of the machine line?


2008
Process Planning Optimization in Reconfigurable Manufacturing Systems
By Farayi Musharavati
2008
https://books.google.co.in/books?id=ab6iQ-4SG5wC&printsec=frontcover#v=onepage&q&f=false

1996
Introduction to Machining Science
Prof G.K. Lal
IIT Kanpur
https://books.google.co.in/books?id=MTiwBJ5VbtYC&printsec=frontcover#v=onepage&q&f=false




1973

Proceedings of the Fourteenth International Machine Tool Design and Research Conference
S. A. Tobias
Macmillan International Higher Education, 1973 - Engineering - 841 pages
https://books.google.co.in/books?id=bFVdDwAAQBAJ

Updated 29.12.2023, 19.4.2022,   8.1.2022,  17.12.2021, 8.5.2021,28 May 2020, 17 May 2020,  2 May 2020
First published 27 April 2020


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Wednesday, December 27, 2023

SMART Goals for Industrial Engineering

 


SMART Goals for Industrial Engineering. Industrial engineering is cost reduction through productivity improvement resources. Some resources are used as time-based resources. Some resources are consumed on quantity basis. Each resource has cost and IEs have to minimize them to produce required output at the quality and other requirements that customers demand. The cost reduction goals has to be in percentage terms on the current costs. The potential cost reduction can be estimated through pilot studies, supplier information and benchmarking information.   


Are you doing it?

PRODUCT INDUSTRIAL ENGINEERING  - FACILITIES IE   - PROCESS IE  

https://academia.edu/103626052/INTRODUCTION_TO_MODERN_INDUSTRIAL_ENGINEERING_Version_3_0


https://www.linkedin.com/advice/3/how-can-you-align-your-work-companys-goals-hk0cf#understand-the-company's-goals

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Tuesday, December 26, 2023

Industrial Engineering in Civil Engineering

Ubiquity of Industrial Engineering Principle - Industrial Engineering is applicable to all branches of engineering.

Industrial Engineering is applicable in all branches of engineering - Principle of Industrial Engineering

View the presentation  "Principle of Industrial Engineering"


_________________

_________________



Industrial Engineering in Civil Engineering



Frank Gilbreth is an important pioneer in the field of industrial engineering. He is primarily concerned with building construction field and applied the scientific management/productivity management/industrial engineering methods and techniques in civil engineering field.

Frank B. Gilbreth: Some of His Industrial Engineering Achievements

MOTION STUDY - Frank B. Gilbreth - Part 1

1985

Laufer, A. (1985). Multiple productivity objectives on construction sites. Project Management Journal, 16(1), 68–75.
https://www.pmi.org/learning/library/multiple-productivity-objectives-construction-sites-5238

2011

Optimization

Rural Connectivity Using CLUSTAL Algorithm
CLUSTAL is cluster analysis approach for optimal rural road network planning.
Indian Highways, June 2011
M.S. Amarnath, A.K. Raji. and V.U. Rejani



Applications of Industrial Engineering in Mexican Construction Industry - Work Shop Proposal
Jorge Cossio made the above workshop proposal.
Systems Integration
Chapter in Modern Construction Book
A case study of application of IE in construction projects - One of the implementors was Jorge Cossio.


Construction Management Productivity Management - Course Page
http://courses.engr.wisc.edu/cee/cee592.html





2012

Application of a Design Method for Manufacture and Assembly
Flexible Assembly Methods and their Evaluation for the Construction of Bridges
Master of Science Thesis in the Master’s Programme Design and Construction Project Management
MICHEL KALYUN
TEZERA WODAJO
Department of Civil and Environmental Engineering - Division of Structural Engineering
Steel and Timber Structures
CHALMERS UNIVERSITY OF TECHNOLOGY
Göteborg, Sweden 2012
http://www.pantura-project.eu/Downloads/Application_of_a_Design_Method_for_Manufacture_and_Assembly_WP4_Master%E2%80%99s%20Thesis%20201229.pdf

2013
Australia - BUILDING AND CONSTRUCTION INDUSTRY (IMPROVING PRODUCTIVITY) BILL 2013
https://www.pm.gov.au/media/2016-08-31/building-and-construction-industry-improving-productivity-bill-2013

2016
Productivity in building design and construction
https://www.designingbuildings.co.uk/wiki/Productivity_in_building_design_and_construction

Australia - Building and Construction Industry (Improving Productivity) Act 2016
https://www.legislation.gov.au/Details/C2017C00042

A study of best management practices for enhancing productivity in building projects: construction methods perspectives
http://epress.lib.uts.edu.au/journals/index.php/AJCEB/article/view/4882/5562

Singapore Government to step up construction productivity using technology
http://www.straitstimes.com/singapore/government-to-step-up-construction-productivity-using-technology

2017

Cost control in building design and construction
https://www.designingbuildings.co.uk/wiki/Cost_control_in_building_design_and_construction

Singapore - Project Productivity
https://www.bca.gov.sg/Productivity/site_productivity_statistics.html

Factors Affecting Productivity in Green Building Construction Projects: The Case of Singapore
http://ascelibrary.org/doi/abs/10.1061/%28ASCE%29ME.1943-5479.0000499


Australia - Building and Construction Industry (Improving Productivity) Amendment Bill 2017
http://www.aph.gov.au/Parliamentary_Business/Bills_Legislation/Bills_Search_Results/Result?bId=r5806

How Can Cloud Technology Boost Productivity and Safety in Construction?
http://www.initiafy.com/news/how-can-cloud-technology-boost-productivity-and-safety-in-construction

Singapore - AMENDMENTS TO BUILDING CONTROL (BUILDABILITY AND
PRODUCTIVITY) REGULATIONS 2011 TO FURTHER RAISE
CONSTRUCTION PRODUCTIVITY
https://www.corenet.gov.sg/media/2033068/circular-on-amendments-to-bc-buildability-and-productivity-.pdf

2019

https://1civilengineering.blogspot.com/2019/06/prefabrication-standardization.html


Product Industrial Engineering in Civil Engineering

Value Engineering - Cement and Concrete - Construction - Bibliography


2023

Construction Productivity Management - CMU Notes - Books - Articles and Papers


The Role of Industrial Engineering in Optimizing Resource Efficiency in Sustainable Construction
26 Oct 2023
12 mins to read








Updated 11.5.2023, 25.4.2022, 26 October 2019, 2 June 2019, 4 July 2017,   14 June 2015
First published 11 Jan 2012






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Monday, December 25, 2023

What is lacking in Industrial Engineering? - A LinkedIn Survey

 9.12.2023


What is lacking in Industrial Engineering?

https://www.linkedin.com/posts/narayana-rao-kvss-b608007_industrialengineering-activity-7139107873980141568-huXX 



Strategy 


Engineering


Management


Research/Science


What is lacking in Industrial Engineering?  40 Votes in 2 weeks - Percentages

Strategy          48%

Engineering       13%

Management        13%

Research/Science  28%


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

Industrial Engineering Departments have to prepare strategy document and implement it.

Industrial Engineering Strategy - Enterprise Level Industrial Engineering

https://nraoiekc.blogspot.com/2014/11/industrial-engineering-strategy.html






Ud. 25.12.2023

Pub. 9.12.2023

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Tuesday, December 19, 2023

New Lighthouse Factories Industry 4.0 December 2023 - Significant Growth and Productivity Benefits

 ACG Capsules (Pithampur, India): 


To stay ahead of the curve in an intensely competitive market, pharmaceutical supplier ACG Capsules prioritized manufacturing superior-quality products, improving responsiveness, increasing production yields and enhancing workforce productivity. To achieve this, ACG Capsules implemented 25+ Fourth Industrial Revolution use cases powered by the industrial internet of things (IIoT), machine learning (ML), deep learning (DL), digital twins, extended reality and generative AI. Effective adoption of these use cases has resulted in a reduction in critical defects of 98%, a shortening of production lead times of 39%, a drop in total losses of 51% and a 44% rise in workforce productivity.



Agilent (Waldbronn, Germany): 


Amid demand fluctuations, strong growth of more than 50%, supply-chain disruptions and evolving product needs, Agilent Waldbronn introduced more than 25 Fourth Industrial Revolution-related roles and 20 associated use cases to address the challenges. Its high-volume and high-mix life-science manufacturing platform benefited from solutions from its Fourth Industrial Revolution toolkit, including AI applications and IIoT for rapid simulation and prediction. The facility has achieved a 35% increase in quality, a 44% boost in productivity and a 48% rise in output, ultimately enabling market share growth.



AMOREPACIFIC (Osan, South Korea): 


To stand out in the cosmetics industry, global beauty company AMOREPACIFIC used Fourth Industrial Revolution technologies such as AI and 3D printing to optimize manufacturing process design, accelerate new product introductions and improve flexibility. This reduced new product lead time by 50% and defects by 54%. It also enabled a new business model for manufactured-in-store customized cosmetics, with over 800,000 unique products offered.



Aramco (Yanbu, Saudi Arabia): 


To maintain a competitive edge as one of the leading suppliers of fuels while minimizing its carbon footprint, this 1970s Aramco refinery underwent a five-year strategic Fourth Industrial Revolution transformation, implementing and integrating use cases at scale including an AI-based clean fuels optimizer, an AI-powered operation decision system and a digital twin dynamic model. As a result, on-spec fuel production has reached 99%, greenhouse gas (GHG) emissions have been reduced by 23% and operational availability has improved by 17%.



CATL (Liyang, People’s Republic of China): 


To address soaring demand and increasing labour costs, and to meet its carbon neutrality commitment, CATL Liyang applied big data to simulate quality-testing, additive manufacturing to reduce changeover times, computer vision to achieve micron-level quality inspection, and deep learning to optimize process controls and energy management. This has resulted in a 320% output increase, a 33% reduction in manufacturing costs, a 47.4% reduction in normalized emissions and a 99% reduction in quality defects. Defect measurement has been upgraded from “per million” to “per billion”.



CITIC Pacific Special Steel (Jiangyin, People’s Republic of China): 

To meet the fast-growing global demand for customized steel products while navigating volatile raw material and energy-supply issues, CITIC Pacific Special Steel’s Jiangyin Xingcheng plant deployed 40+ Fourth Industrial Revolution use cases such as advanced analytics-powered process simulation and optimization, as well as AI-enabled energy management. As a result, the plant has been able to increase customized orders by 35.3%, reduce its non-qualified product rate by 47.3% and cut its energy consumption by 10.5% per tonne of steel.



China Resources Building Materials Technology (Tianyang, People’s Republic of China): 

To address the requirements of green and low-carbon development, higher quality expectations and cost pressures, Tianyang site, a cement factory under China Resources Building Materials Technology Holdings, has deployed 30+ Fourth Industrial Revolution use cases with advanced analytics, autonomous driving and IIoT to improve energy, labour and equipment efficiency and quality performance. As a result, the site has reduced carbon emissions by 24%, increased labour productivity by 105%, reduced unplanned downtime by 56% and improved quality consistency by 25%.



GAC AION (Guangzhou, People’s Republic of China): 

To satisfy customers’ spiking demand for reliable and customized electric vehicles, GAC AION deployed 40+ Fourth Industrial Revolution use cases to provide customers with more than 100,000 configuration options and ensure timely and qualified deliveries. The fully automated production line supports mixed production of made-to-order and made-to-stock models, increasing production efficiency by 50%, reducing delivery times by 33%, raising first-pass yields by 8% and reducing manufacturing costs by 58%.



Haier (Hefei, People’s Republic of China):

 The rise of a new middle class and increased consumer consumption in China have driven upgrades from a split air conditioner (AC) system to a central AC system, which has higher requirements in terms of quality and energy efficiency. Haier’s Hefei air conditioner factory applied advanced algorithms, digital twins, knowledge graphs and other cutting-edge technologies in the research and development (R&D), production and testing of household central AC systems, resulting in a 33% increase in energy efficiency, a 58% drop in the defect rate, a 49% increase in labour productivity and a 22% drop in unit manufacturing costs.



Hengtong Alpha Optic-Electric (Suzhou, People’s Republic of China): 

Facing higher cost pressures as well as quality and green production expectations from the international market, Hengtong Alpha accelerated the large-scale application of advanced analytics, machine vision and AI technology across 27 advanced use cases covering the whole production value chain. As a result, unit manufacturing costs have decreased by 21%, the defect rate has reduced by 52% and unit power consumption has fallen by 33%.



Ingrasys, Foxconn Industrial Internet (Taoyuan, Taiwan, People’s Republic of China): 

The rapid development of AI foundation models has brought an explosion in demand for computing power and higher efficiency, quality and iteration speed requirements for AI servers. By deploying AI use cases across order forecasting, warehouse and production scheduling, product design, quality and assembly-testing domains, Foxconn Industrial Internet’s Taiwan factory has achieved a 73% increase in production efficiency, a 97% reduction in product defects, a 21% reduction in lead time and a 39% decrease in unit manufacturing costs.



K-water (Hwaseong, South Korea): 

The climate crisis has caused significant water supply concerns, as heatwaves and heavy rains create more volatile and turbid supplies. To address this, K-water launched a next-generation AI water treatment plant to reduce production costs, improve responsiveness and reduce human error. It is being scaled across 40+ other sites and has helped K-water to reduce its chemical usage by 19%, improve labour efficiency by 42% and reduce power consumption by 10%.



LONGi Solar (Jiaxing, People’s Republic of China): 

Driven by the desire to reduce costs, improve quality and shorten the lead time on solar modules, the Jiaxing site implemented more than 30 Fourth Industrial Revolution use cases, using AI and advanced analytics to boost manufacturing operations. These efforts have had significant impacts, with the site achieving a 28% reduction in unit manufacturing costs, a 43% cut in yield loss and an 84% decrease in production lead time within one year, while also lowering energy consumption by 20%.



Mondelēz (Beijing, People’s Republic of China): 

Embracing sustainability ambition from both Mondelēz Global and Beijing City while meeting Mondelēz’s growth ambitions and addressing operating cost pressures due to year-on-year (YoY) 6% labour cost inflation, Mondelēz Beijing implemented 38 Fourth Industrial Revolution use cases, such as an AI-powered dough-making lights-off workshop and gas consumption optimization by machine learning. As a result, Mondelēz Beijing has achieved a 28% net revenue growth and 53% increase in labour productivity while reducing GHG emissions by 24% and food waste by 29%.



ReNew (Ratlam, Madya Pradesh, India): 

To maximize productivity, streamline costs and redeploy the existing workforce to help in-source operations and maintenance (O&M) capabilities, renewable energy company ReNew built on and scaled the digital and analytics backbone from its first Lighthouse site, including new proprietary AI models and the rapid scaling of Fourth Industrial Revolution use cases across 70 wind farms, 10 original equipment manufacturers (OEMs) and 22 unique wind turbine models. Ratlam, the company’s benchmark site for this scale transformation, has sustained improvements of 1.7% higher energy yield, 17% reductions in operating expenses and 40% less waste. This led to a 20% increase in profitability.



VitrA Karo (Bozüyük, Türkiye): 

Increased energy prices and inflation have affected energy costs and the labour-intensive ceramic tile production process. To sustain competitiveness while responding to higher demands and maintaining a complex portfolio of 4,200+ SKUs, VitrA Karo’s Bozüyük site deployed its digital transformation roadmap, focusing on intelligent process and production controls. This has resulted in a 19% increase in OEE, a 56% decrease in scrap, a 14% decrease in energy consumption and a 43% increase in the use of recycled content.



End-to-End (E2E) Value Chain Lighthouses



DHL Supply Chain (Memphis, Tennessee, United States): 

Facing a growing e-commerce market and driven by retail promotions and a consumer consumption switch from offline to online orders, in addition to heavy seasonality impacts, DHL Supply Chain in Memphis, Tennessee established a strategic Fourth Industrial Revolution site, equipped with a control tower for centralized planning and execution oversight to manage and control E2E operations. This site has seamlessly integrated robots, analytics and a flexible staffing solution, resulting in a 50% overtime reduction, a 57% shipment cycle time reduction and a 290% increase in capacity, leading to a 28% compound annual growth rate (CAGR) since 2019. Consequently, the site has emerged as a primary training hub for the global adoption of new technologies.



Haier (Qingdao, People’s Republic of China): 

To stay ahead of the industry on cost and address common problems of unprofessional and delayed services in the home-appliance industry, Haier deployed 136 Fourth Industrial Revolution use cases for procurement cost savings and improvements in productivity and quality of services, using technologies including 5.5G, advanced algorithms and ready-to-use digital twins. This initiative has resulted in product cost being optimized by 32%, labour productivity increasing by 36% and the service complaint rate being cut by 85%.



Johnson & Johnson (Xi’an, People’s Republic of China): 

To improve agility and responsiveness, raise quality standards and enhance competitiveness, Johnson & Johnson Xi’an replaced its manual facility with a Fourth Industrial Revolution-enabled new factory in 2019. This facility includes digital twins for technology transfer and material handling, intelligent automation of continued process verification (CPV) and batch execution processes. This has shortened the product transfer time by 64% during site relocation and has enabled a 60% decrease in non-conformance, while improving productivity by 40%, operating costs by 24% and GHG emissions by 26%.



Kenvue (Shanghai, People’s Republic of China): 

To keep up with the growth in e-commerce, faster speed to market and the fluctuating demands that come from increased cost competitiveness, Kenvue Shanghai deployed more than 25 Fourth Industrial Revolution use cases, including big data analytics on social media, digital twins, additive manufacturing and ML across its E2E value chain. This resulted in a 50% reduction in new product introduction lead times, 1.3-times improvement in forecast accuracy and 99.8% on-time-in-full deliveries within 48 hours. This enabled the e-commerce business to double from 30% to 60% of overall business.



Unilever (Sonepat, India): 

To improve agility and cater to diverse product segments, reduce costs in an inflationary environment and improve sustainability, Unilever Sonepat implemented 30+ Fourth Industrial Revolution use cases in its E2E supply chain. Top use cases included boiler and spray dryer process twins, as well as customer data-informed no-touch production planning and inventory optimization. This improved service by 18%, forecast accuracy by 53%, conversion cost by 40% and Scope 1 carbon footprint by 88%. The use of biofuels enabled by a boiler process twin also supports livelihoods for local farmers.

https://www.weforum.org/press/2023/12/factories-of-the-future-show-how-to-apply-ai-to-benefit-people-planet-and-performance/

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Chat with AI ChatBot of Bob Emiliani on Industrial Engineering

 


https://bobemiliani.com/introducing-my-ai-chatbot/


18.12.2023


I want to know how you use industrial engineering


Industrial Engineering (IE) is used as a system to analyze and improve productivity, reduce costs, and enhance quality. It involves the use of tools like time and motion studies to understand how people work and establish a baseline for improvements. This was the foundation for the development of Toyota's unique IE-based kaizen method, which was instrumental in improving their productivity post World War II.

IE is not just about technological innovation or mechanization of production through capital investment. It focuses on improving labor productivity via process improvement using existing machines, tools, and materials. This involves observing processes on the shop or office floor, asking why within the framework of the 7 wastes, and discovering knowledge to eliminate waste, unevenness, and unreasonableness.

However, it's important to note that the application of IE methods should always respect the "Respect for People" principle. Training your people in IE methods and never losing sight of this principle is key to replicating the success of companies like Toyota.


I think respecting people is advocated by Taylor and Gilbreth also.


Absolutely, you're correct. Both Frederick Winslow Taylor and Lillian Gilbreth were pioneers in the field of management and industrial engineering, and their work laid the foundation for modern management systems.

Taylor, often misunderstood and misrepresented, was actually a proponent of scientific management, which aimed to improve efficiency and productivity. He believed in hard work, getting your hands dirty, knowing the job, doing experiments scientifically, and being creative. His work was a necessary first step in the evolution of progressive management that helped pave the way for Toyota’s management system decades later.

Lillian Gilbreth, on the other hand, was one of the first female engineers to earn a Ph.D. She was a pioneer in the field of industrial and organizational psychology and made significant contributions to industrial engineering. Her work also emphasized the importance of the human element in the workplace.

However, it's important to note that while these pioneers laid the groundwork, the "Respect for People" principle was further developed and emphasized in the Toyota Production System (TPS). This principle is integral to Lean management and cannot be disconnected from the concept of flow in TPS.

For more insights, you can check out these blog posts: Leading Without Respect, Yasuhiro Monden, and The Lean Movement's Strategic Errors.

bot avatar


https://bobemiliani.com/leading-without-respect/


https://bobemiliani.com/yasuhiro-monden/


https://bobemiliani.com/the-lean-movements-strategic-errors/

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