Wednesday, April 5, 2023

Computer Aided Industrial Engineering (CAIE) - IE Now in CIM - Prof. Narayana Rao K.V.S.S.


Scholarly Journal,  IIE Annual Conference 2021 Proceedings.

Industrial Engineering 4.0 - Computer Aided Industrial Engineering: Work Systems Analysis in Industry 4.0

Rao, Kambhampati Venkata Satya Surya Narayana; Rathod, Aniket. IIE Annual Conference. Proceedings; Norcross (2021): 49-54.

https://www.proquest.com/openview/d32ef32bbaa911d170e046479790c035/1

 


About Dr. K.V.S.S. Narayana Rao (Narayana Rao Kambhampati) 





Dr. K.V.S.S. Narayana Rao (Narayana Rao Kambhampati)  is presently Professor in National Institute of industrial Engineering (NITIE), Mumbai, India. He did his post graduation in industrial engineering from NITIE, Mumbai in 1979. His doctoral research is in the area of financial economics in the discipline of industrial management from IIT, Bombay. Prof. Rao published number of papers in both industrial engineering and investment analysis.


Prof. Narayana Rao made efforts in understanding the evolution of industrial engineering discipline since 1994, when he first heard adverse comments on the discipline in an alumni meeting of industrial engineering postgraduates. After making number of conference presentations and publishing papers, he presented the "Principles of Industrial Engineering" in the 2017 Annual Conference of IISE. He developed functions and focus areas of industrial engineering that are aligned to the principles. His blog, Industrial Engineering Knowledge Center, https://nraoiekc.blogspot.com, is a global top blog. The blog is visited by more than 106,000 industrial engineers. His YouTube Channel, having video presentations on industrial engineering, is also a popular channel. He is presently developing an online course on industrial engineering in his blog.


Dr. Rao advocates the objectives of industrial engineering as system efficiency engineering and human effort efficiency engineering. Industrial engineering is continuous improvement in engineering systems to increase productivity. It is an engineering discipline taking care of product and process life cycle engineering and management of productivity. In the area of work systems design and productivity improvement, he advocates two areas, machine work system and human work system. In the present engineering systems, the role of machine or engineering is very high and industrial engineers have to increase focus on engineering elements substantially compared to the current emphasis. Industrial engineers have to update their engineering knowledge throughout their life.  Industrial engineering to make the transition to industrial engineering 4.0 and computer aided industrial engineering has to emerge as popular practice in industrial engineering.


Industrial Engineering 4.0 - Computer Aided Industrial Engineering: Work Systems Analysis in Industry 4.0

Important Points Covered in the Paper

Manufacturing execution systems (MES) and Industrial Engineering

1.Introduction

In the progress of engineering, the role of computers has increased in the engineering systems design, production and operation.  Computer aids to industrial engineering also came into existence. But it did not evolve into “computer aided industrial engineering” (CAIE).

Manufacturing execution systems (MES) store product and process data and also record the manufacturing events. The recorded data can be utilized by IEs to develop process charts and information on machine effort and human effort to study the process to  increase productivity. Computer aided industrial engineering (CAIE) can be made the main method in industrial engineering practice in industrial engineering 4.0.


2. What is Industrial Engineering?

Industrial engineering’s origin is F.W. Taylor’s productivity improvement in machine shops by developing science of metal cutting productivity. Taylor started a section with the name "Rate Fixing Department" that evolved into IE department.

Then it was generalized to other engineering activities and to purely manual activities.

In 1893, he presented paper on the redesign of belts to minimize the cost.  In 1895, complete system of productivity improvement in machine shop was presented. It involved study of engineering elements: machine effort elements and human effort elements. 

What are typical machine elements? You can understand it from the popular subject, "Design of Machine Elements." Cutting tools are elements in machining and machine tool. Even angles of cutting tools are elements. Even insert shape is an element. Industrial engineers have to go down to the lowest level to seek productivity improvement opportunities and modify every element where improvement is possible.The purpose is to identify the best alternatives to increase the productivity. The objective is to reduce machine time and man time. 

Taylor recommended creation of a new department the “elementary rate fixing department.” It became industrial engineering department in due course.

James Gunn, a Harvard B-School faculty member, gave the name industrial engineer (IE). IE understands the costs created by engineering decisions and reduces them to the minimum by selecting the best engineering alternatives. Industrial engineering became continuous engineering improvement of processes based on shop floor studies. 

The primary focus of industrial engineering is cost reduction and productivity improvement.


Other performance areas were also added or attempted by industrial engineers to augment their scope of activity. In the effort to increase productivity, Taylor and Gilbreth insisted that quality and human comfort should not suffer. Principles of industrial engineering presented in IISE 2017 Annual Conference by Narayana Rao,  capture important issues that are part of industrial engineering discipline at the current time. 

Now industry 4.0 is being welcomed by IEs and industrial engineering 4.0 was already proposed.


3.Computers in Industrial Engineering Methods

Ralph Barnes, in his seventh edition of Motion and Time Study devoted two chapters to explain the role of computers in industrial engineering. Chapter 25 is titled “computer aided time study.” Chapter 26 is titled “computerized machine and equipment downtime monitoring and reporting” [Barnes]. Time study is an important method in IE and it is important to notice that in 1980 itself, the role of computers was discussed in time study. In the area of layout planning also, computer methods existed during the 70s. 


4.Computer Aided Process Charting, Study and Improvement - Is It Possible?

In the current popular practice, process improvement or method studies have to be done by IEs by observing the process on the shop floor. In addition, they can collect more information from various files. The mechanization and automation have increased in engineering systems. Computer control, PLC control and DCS have emerged.  Manufacturing execution systems (MES) came into existence to convert orders on the factory released by MRP system into jobs scheduled for individual machines. The output of MES is routed to machines through DCS/PLCs and each action taken by each device in the machine is now recorded. Hence the device identification and the action that it has taken are available in MES records. The manual activity is also collected by the MES through human machine interfaces (HMI). From these records, details of all elements of the process, the devices used and the parameters that were set by them in the operation/process can be extracted for method study or process improvement. Thus the recording activity of the method study can  totally become computer aided activity. Each event has a time stamp and this can give a wealth of time data for each event. 


5.Process Productivity Improvement Using Data From Manufacturing Execution Systems

Manufacturing Execution System (MES) is a process-oriented manufacturing planning, directing, recording and controlling information technology system. It maintains a database of products, various operations to be done to produce the products, various resources required to do the processing, orders received from customers or from MRP system, and other related data.

MES systems report the losses of machine time, operators’ time and material in real time to initiate supervisory actions to prevent furthers losses [MES]. The data recorded in MES about the losses facilitates root cause analysis. Industrial engineers can develop engineering changes and management policy changes based on the issues brought out in the root cause analysis. The problems in the equipment and the pain points of operators captured in the MES are addressed by industrial engineers as required by engineering changes in equipment as well as in the process. These modules of MES contribute to work systems analysis for productivity improvement.

Industrial engineers can prepare process charts and operation information sheets from the MES data and investigate the operations for further improvement based on the new engineering knowledge.

Thus, we can see clearly the role of MES in providing the data and visualization support for process improvement. As industrial engineers start using MES more actively, modifications can be proposed and got implemented for enhancing the utility in process improvement studies.

6. Process Productivity Improvement Through Process Mining 

Process mining, a data science task, also supports process improvement.  In process mining manifesto, van der Aalst W. et al. (2012) state that the idea of process mining is to discover, monitor and improve processes by extracting knowledge from the event logs readily available in today’s information  systems like ERP and MES [PM]. Process mining includes current process discovery, conformance checking (i.e., monitoring deviations by comparing the specified process and actual events recorded in the log), organizational mining (activities of persons), automated construction of simulation models, model extension, model repair, case prediction, and history-based recommendations.


Process mining is an enabling technology for business process improvement (BPI). Process mining is successfully  applied in number of manufacturing processes also. The objective of process mining is explicitly process improvement. 


7. Process Productivity Improvement Using Digital Twins 

Digital twin is a digital copy of a real factory, assembly line or  machine,  etc., that is created and automatically updated with the data sent by sensors on the machines and robots. Once created, the digital twin is globally available in real time to study the important aspects of the physical machine and simulate various changes. In the digital twin, the current information as well as historical information and simulations conducted are available to make use of in product and process designs as well as in planning operations related to doing jobs.

Descriptions of more applications of digital twins in manufacturing are available.  The applications include improvement of product manufacturing process, production process optimization and fault diagnosis, and modeling for energy optimization. All there areas are the responsibility of industrial engineers to maintain and improve productivity and efficiency of production systems. Industrial engineers have to adopt digital twin in the process and work systems improvement and do further research to enhance  the use of digital twin in process improvement. 

8. Knowledge Management for Industrial Engineering

Industrial engineering has to generate alternatives for performing various elements of current processes to improve productivity and quality. In more general terms, it is to increase efficiency while maintaining the effectiveness of processes to produce products and services that are in demand. To do it successfully, the knowledge of engineering and technology developments are to be creatively combined with process requirements. There has to be a system that acquires technology developments on a continuous basis and makes it available to all persons in the organization to drive process improvement thinking. Further, artificial intelligence can be employed to locate the news and information that has  direct application in specific operations of the processes. 

9. Conclusion

Multiple ways of collecting data for visualizing processes are available now in software systems being used in manufacturing. Some of these systems explicitly state “supporting process improvement” as one of their objectives. These systems were introduced to industrial engineers in some articles published in IISE magazine. The Industrial Revolution 4.0 (Industry 4.0) has increased digitization in manufacturing and there is a trend toward collecting data from all machines and related accessories through embedded sensors. Industrial engineers can utilize more computer assistance now to do process data recording and to simulate improvement ideas. In the industrial engineering practice in industry 4.0 systems, a structured computer assisted industrial engineering is possible and the profession has to deliberate on it and develop a suggested initial practice which can be further improved after evaluating the experience. 

The Industrial Revolution 4.0 (Industry 4.0) has increased digitization in manufacturing.

Data from all machines,   related accessories, jobs and operators is collected through embedded sensors and MES. 

Industrial engineers can utilize more computer assistance now to do process data recording, process charting, experimenting with improvement ideas through simulation and time standard setting.

Software modules and systems to be included in Computer Aided Industrial Engineering System

1. Work Measurement Software.

2. Shop Layout Software

3. Machine Downtime Monitoring

4. MES

5. Process Mining

6. Digital Twins

7. Knowledge Management

8. Simulation


Thank you Prof. Shahrukh Irani for the presentation,  "A Framework for Selecting IE Software" shared on LinkedIn through a post.  https://www.linkedin.com/posts/shahrukh-irani-8b25a55_a-framework-for-selecting-ie-software-to-activity-7049149625546534913-pmcr



New addition (2021): “Data-driven throughput bottleneck analysis in production systems." - PhD Thesis - It will be part of computer aided industrial engineering.

Mukund Subramaniyan - Ph.D. from Chalmers University

Presentation - Computer Aided Industrial Engineering (CAIE) - Prof. Narayana Rao K.V.S.S.


Industrial Engineering 4.0 – Computer Aided Industrial Engineering: Work Systems Analysis in Industry 4.0 - IISE 2021 Annual Conference Paper

Prof. K.V.S.S. Narayana Rao (NITIE,India)

(Principles and Functions of IE)

Aniket Rathod (NITIE Alumnus)

Industrial Engineering Knowledge Center

Blog maintained by Prof. Narayana Rao

Global Number One IE Blog

Utilized  by 106,000 industrial engineers

http://nraoiekc.blogspot.com


1. Introduction

In the progress of engineering, the role of computers has increased in the engineering systems design, production and operation. 

Computer aids to industrial engineering also came into existence.

But it did not evolve into “computer aided industrial engineering” (CAIE).


MES and Computer Aided Industrial Engineering

Manufacturing execution systems (MES) store product and process data and also record the manufacturing events. 

The recorded data can be utilized by IEs to develop process charts and information on machine effort and human effort to study the process to  increase productivity.

Computer aided industrial engineering (CAIE) can be made the main method in industrial engineering practice in industrial engineering 4.0.


2. What is Industrial Engineering?

Industrial engineering’s origin is F.W. Taylor’s productivity improvement in machine shops by developing science of metal cutting productivity. 

Then it was generalized to other engineering activities and to purely manual activities.

In 1893, he presented paper on the redesign of belts to minimize the cost.  

In 1895, complete system of productivity improvement in machine shop was presented.

Redesign of Engineering Elements

It involved study of engineering elements: machine effort elements and human effort elements. 

The purpose is to identify the best alternatives to increase the productivity and do productivity engineering  (process IE) and productivity management. 


The objective is to reduce machine time and man time. 


Taylor recommended creation of a new department the “elementary rate fixing department.” (Became IE in due course)

James Gunn – Industrial  Engineer – Understands Costs

James Gunn, a Harvard B-School faculty member, gave the name Industrial Engineer (IE).

IE understands the costs created by engineering decisions and reduces them to the minimum by selecting the best engineering alternatives.

Industrial engineering became continuous engineering improvement of processes based on shop floor studies (Basic design and Redesign). 

The primary focus of industrial engineering is cost reduction and productivity improvement.


Other Performance Areas – Continuous Improvement

Other performance areas were also added or attempted by industrial engineers to augment their scope of activity. 

In the effort to increase productivity, Taylor and Gilbreth insisted that quality and human comfort should not suffer.

Principles of industrial engineering presented in IISE 2017 Annual Conference by Narayana Rao capture important issues that are part of industrial engineering discipline at the current time.

Now industry 4.0 is being welcomed and industrial engineering 4.0 was already proposed.


3. Computer Support in Industrial Engineering Methods

Ralph Barnes

Motion and Time Study (7 ed.) by Ralph Barnes contains,  

Chapter 25 - “computer aided time study,” and 

Chapter 26  “Computerized machine and equipment downtime monitoring and reporting.” 

In the area of layout planning, computer methods existed during the 70s. 


4. Computer Aided Process Charting, Study and Improvement - Is It Possible?

In the current popular practice, process improvement or method studies have to be done by IEs by observing the process on the shop floor.

The mechanization and automation have increased in engineering systems. 

Computer control, PLC control and DCS have emerged. 

Manufacturing execution systems (MES) came into existence to   schedule jobs for individual machines and operators and transmit instructions to them. 


MES Input Data – Recorded Data 

MES records each action taken by each device/machine and each operator. 

From these records, details of all elements of the process, the devices used and the parameters that were set by them in the operation/process can be extracted for method study or process improvement. 

Thus the recording activity of the Process improvement/method study can totally become computer aided activity. 

Each event has a time stamp and this can give a wealth of time data for each event. 


5. Process Productivity Improvement Using Data From Manufacturing Execution Systems

Manufacturing Execution System (MES) is a process-oriented manufacturing planning, directing, recording and controlling “information  system.” 

It maintains a database of products, process plans, resource requirements, orders received, and other related data.

MES systems report the losses of machine time, operators’ time and material in real time.  

The data about the losses facilitates root cause analysis. 


MES Supports Work Systems Analysis

Industrial engineers can develop engineering changes and management policy changes to prevent losses. 

The problems in the equipment and the pain points of operators can be addressed by IEs. 

The modules of MES contribute to work systems analysis for productivity improvement.


Process Charts from MES Data – Possible

Industrial engineers can prepare process charts and operation information sheets from the MES data and investigate the operations for further improvement based on the new engineering knowledge.

To summarize, MES provides the data for developing process charts to support process improvement.

As industrial engineers start using MES more actively, modifications can be proposed and got implemented for enhancing the utility in process improvement studies.

6.Process Productivity Improvement Through Process Mining

Process mining, a data science task, also supports process improvement.

Process mining is used to discover, monitor and improve processes by extracting knowledge from the event logs available in ERP and MES. 

Process mining is an enabling technology for business and manufacturing process improvement (BPI). 

The objective of process mining is explicitly process improvement.

7. Process Productivity Improvement Using Digital Twins

Digital twin is a digital copy of a real factory, assembly line or machine.

It is created and automatically updated with the data sent by sensors on the machines, robots, workpieces. 

Once created, the digital twin is globally available in real time to study the important aspects of the job, physical machine and its operation. 

It can be used to simulate various changes.

Applications of Digital Twins in Manufacturing

In the digital twin, the current and historical information and simulations conducted are available to make use of in product and process designs as well as in planning operations. 

The applications of digital twins include improvement of product manufacturing process, production process optimization and fault diagnosis, and modeling for energy optimization. 

All there applications help industrial engineers to improve productivity and efficiency of production systems.

8. Knowledge Management for Industrial Engineering

Industrial engineering has to generate better engineering alternatives

To do it successfully, the knowledge of engineering and technology developments are to be creatively combined with process requirements. 

IE requires a system that helps it to record and monitor technology developments. 

Artificial intelligence can be employed to locate the news and information that has direct application in specific operations of the processes from the knowledge bases maintained.

Software Systems Indicated

1. Work Measurement Software.

2. Shop Layout Software

3. Machine Downtime Monitoring

4. MES

5. Process Mining

6. Digital Twins

7. Knowledge Management

8. Simulation

9. Conclusion and Thanks

The Industrial Revolution 4.0 (Industry 4.0) has increased digitization in manufacturing.

Data from all machines,   related accessories, jobs and operators is collected through embedded sensors and MES. 

Industrial engineers can utilize more computer assistance now to do process data recording and process charting. 

A structure for  computer assisted industrial engineering is to be developed.  

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


(C) K.V.S.S. Narayana Rao 2021  - Permission given to IISE to publish the paper in the IISE 2021 proceedings.

Full Schedule of the Conference

https://www.eventscribe.net/2021/IISEAnnual/agenda.asp?startdate=1/1/2021&enddate=1/1/2021&BCFO=&pfp=&tn=&cpftwo=&custwo=&pta=


https://www.iise.org/Annual/details.aspx?id=10042

Industrial engineers can prepare better CAPP algorithms that give more-productivity process plans.

Computer-Aided Process Planning (CAPP) - Introduction.

Digital Twins of CNC Machines - Bibliography



Additional References

McLean, C. (1993), Computer-Aided Manufacturing System Engineering, Proceedings of the IFIP TC5/WG5.7 International Conference on Advances in Production Management Systems APMS '93, [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=821349 (Accessed September 19, 2021)

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


A manufacturing system design framework for computer aided industrial engineering

Maurice Bonney, Michael Head, Svetan Ratchev & Idir Moualek

International Journal of Production Research 

Volume 38, 2000 - Issue 17

This paper describes a framework that formalizes within a concurrent engineering approach, performing  the functions of industrial engineers, ergonomists and process planners. The paper describes and illustrates how a workplace may be designed. The emphasis of the work is the design of human centred manual assembly systems. The overall objective of the work is to improve the process of manufacturing systems design by the concurrent efforts of industrial engineers, ergonomists and process planners.

https://www.tandfonline.com/doi/abs/10.1080/00207540050205118


Experiences in Continuous Improvement of “Computer-Aided Manufacturing Systems”
Richard Jerz, St. Ambrose University

Design of a semiautomated system for capturing and processing shop floor information
Gayle L.Berry,  David  Jung ,  David D.Bedworth,    Hewitt H.Young

Journal of Manufacturing Systems
Volume 2, Issue 1, 1983, Pages 39-52

Abstract
This paper presents an overview of a United States Air Force Integrated Computer-Aided Manufacturing project devoted to the design of a shop floor information system. The key to effective automated and nonautomated manufacturing operations is the capture of raw, accurate, and timely shop floor data for effective process, monitoring control, and decision making. The reader is given a project overview to show how a shop floor information system might be planned, evaluated and designed with both software and hardware characteristics being considered.

David D. Bedworth is a Professor of Engineering in the Department of Industrial and Management Systems Engineering at Arizona State University, Tempe, Arizona, and is immediate past chairman of that department.  His research and teaching interests lie primarily in the areas of computer aided processes and quantitative production control.

Hewitt H. Young is a Professor of Engineering in the Department of Industrial and Management Systems Engineering at Arizona State University, Tempe, Arizona, and was the department chair from 1967–1976. Professor Young is a member of ASEE, and a Fellow of AIIE. He served as a vice president of AIIE from 1973–1975 and 1977–1979.  His principal areas of research and teaching expertise are in computer aided design and manufacturing as well as in industrial engineering analysis and design.
https://www.sciencedirect.com/science/article/abs/pii/S0278612583800077

Ud 5.4.2023.
13.6.2022, 24.3.2022, 12.1.2022, 8.12.2021
Pub 19.9.2021







3 comments:

  1. https://tippie.uiowa.edu/people/richard-j-jerz

    ReplyDelete
  2. thank you for your information. Overall, a realtime monitoring system is a valuable tool for any organization looking to stay competitive and stay ahead of the curve.
    Industry 4.0 Manufacturing Companies

    ReplyDelete
  3. Computer aided drug design software has emerged as a cornerstone in the quest for innovative and effective therapeutics, revolutionizing the way researchers conceptualize, design, and optimize potential drug candidates.

    ReplyDelete