In the IE journals and magazines we need to read articles and papers that point out how IEs are able to come out with solutions to data development challenges of OR models.
Operations Research methods are characterized as efficiency improvement techniques by many scholars.
1. From efficiency measurement to efficiency improvement: The choice of a relevant benchmark, Eduardo González, and Antonio Álvarez, European Journal of Operational Research, Volume 133, Issue 3, 16 September 2001, Pages 512-520
2. Measuring Efficiency in Primary Health Care Centres in Saudi Arabia, ASMA M. A. BAHURMOZ,
http://www.economics.kaau.edu.sa/Faculty_Mag/Magallat/A12A2_PDF/122-ASMA999.pdf
3. Improving Transportation Efficiency at the Nanzan Educational Complexeral Motors
http://www.scienceofbetter.org/can_do/success_stories/iteatnecm.htm
4. Operations Research: The Productivity Engine: How to create unassailable productivity gains in your business, Lew Pringle, OR/MS Today, June 2000
http://www.lionhrtpub.com/orms/orms-6-00/pringle.html
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Synergy Between Industrial Engineering and Operations Research
Industrial engineering is developed by engineers working in engineering departments of business companies engaged in manufacture using machines and metals. No doubt construction which is the earliest engineering activity also contributed in the development of industrial engineering as Frank Gilbreth was from construction sector. Operations Research as a discipline is identified with persons from science background working in the area of military operations. Industrial engineering and Departments of Mathematics and Statistics embraced the discipline of operations research in a big way. What is the synergy between industrial engineering and operations research?
Industrial engineering is system efficiency improvement. It examines proposed ways of doing work and improve them. Operations research has number of efficiency improvement tools. Operations researchers developed various standard models and have the ability to develop custom models that improve the efficiency of operations. Linear programming models, transportation, and assignment can be cited as examples using which the operations of an organization can be evaluated for efficiency of resource use subject to the constraints and optimal or efficient solutions can be found. Hence industrial engineers have to be the first group among various corporate organizations to recognize and implement OR models in the business organizations. This opportunity was correctly identified by the industrial engineering profession and OR was adopted as an important technique in the arsenal of industrial engineering.
What is the Contribution of IE to OR?
Industrial engineers could have promoted the practical utilization of OR by proving data in the form the OR models require. In systems engineering, there is mention of this step. From the synthesized design for a system design problem, various models are to be developed to evaluate the proposed design. To use OR models, various types of data are required and industrial engineers have the advantage of developing the required data. Why IEs have the advantage? Industrial engineers have the advantage because they have a strong attachment to measurement in one of their core subjects work measurement. Industrial engineers also are given inputs in understanding the financial and cost accounting data. Thus they are in the unique position to develop and provide the data that OR models required and come out the most efficient solutions and help the operating managers in implementing the solutions. But this does not seem to have happened in big scale.
The reason for the lack of popularity for OR in many organizations is the lack of this viewpoint in IEs. IEs have to use OR models as efficiency improvement avenues. To use OR models they have to develop the required data from the operations of the organization. They have to interact with the accounting departments meaningfully and acquire the required accounting data and statements. They have to develop engineering data and then use appropriate OR models. In the IE journals and magazines we need to read articles and papers that point out how IEs are able to come out with solutions to data development challenges of OR models.
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Problem Areas for Applying Operations Research
Loading machine centers for maximum utilization of equipment.
Controlling raw materials nd in-process inventories.
Planning the minimum production costs schedules through the sequencing and allocation of men and machines.
Minimizing waiting times between opeartions
Determining the true incremental benefits of adding new production equipment.
Scheduling direct labour.
Determining the most favourable preventive maintenance plans.
Assigning individuals to specific jobs
Specifying least-cost shipment patterns in multiplant multivendor purchasing situations.
Locating warehouses so as to minimize freight and production costs.
Allocating advertising budget in the most efficient manner.
Source:
"Opeartions Research", Chaper 9-3 in Industrial Engineering Handbook, H.B.Maynard (Ed.) 2nd Edition
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Related Knols
Knol Handbook of Industrial Engineering (Year 2010 Version)
By Narayana Rao K.V.S.S.
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Bibliography
OR Models - Good brief description of Linear programming, Network Flow Programming, Integer programming, Nonlinear programming, Dynamic programming, Stochastic programming and Simulation etc.
http://www.me.utexas.edu/~jensen/ORMM/models/index.html
The Periodic Vehicle Routing Problem: A Case Study
http://papers.ssrn.com/sol3/papers.cfm?abstract_id=1368749
A Review of Integrated Analysis of Production-Distribution Systems, 1995
http://www.eng.buffalo.edu/~nagi/papers/ana.pdf
Optimization of Container Process at Multimodal Container Terminals, Phd Thesis, 2008, Andy Wong
http://eprints.qut.edu.au/16626/1/Andy_Wong_Thesis.pdf
Operations Research Models for Railway Rolling Stock Planning, Ph.d thesis, (2006), Gabor Maroti
http://alexandria.tue.nl/extra2/200610302.pdf
IFORS 2002 Conference Proceedings - Abstracts only 285 page file
http://meetings2.informs.org/IFORS2002/working_files/program.pdf
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Recent papers about OR models and applications
The costs of poor data quality
Summary of Anders Haug, Frederik Zachariassen, Dennis van Liempd, "The costs of poor data quality", Journal of Industrial Engineering and Management, 2011 – 4(2): 168-193 – Online ISSN: 2013-0953 Print ISSN: 2013-8423
Article originally posted at
http://knol.google.com/k/operations-research-an-efficiency-improvement-tool-for-industrial-engineers#
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