Operations management

Operations management is concerned with designing and controlling the

It is concerned with managing an entire production system that converts inputs (in the forms of raw materials, labor, consumers, and energy) into outputs (in the form of goods and services for consumers).^[2] Operations management covers sectors like banking systems, hospitals, companies, working with suppliers, customers, and using technology. Operations is one of the major functions in an organization along with supply chains, marketing, finance and human resources. The operations function requires management of both the strategic and day-to-day production of goods and services.^[3]

In managing manufacturing or service operations, several types of decisions are made including operations strategy, product design, process design, quality management, capacity, facilities planning, production planning and inventory control. Each of these requires an ability to analyze the current situation and find better solutions to improve the effectiveness and efficiency of manufacturing or service operations.^[4][5][6]

History

The history of production and operation systems begins around 5000 B.C. when

Services were also performed in the Middle Ages by servants. They provided service to the nobility in the form of cooking, cleaning and providing entertainment. Court jesters were considered service providers. The medieval army could also be considered a service since they defended the nobility.^[citation needed]

The

At the turn of the twentieth century, the services industries were already developed, but largely fragmented. In 1900 the U.S. service industry consisted of banks, professional services, schools, general stores, railroads and telegraph. Services were largely local in nature (except for railroads and telegraph) and owned by entrepreneurs and families. The U.S. in 1900 had 31% employment in services, 31% in manufacturing and 38% in agriculture.[10]

The idea of the

Before the

"The thing is to keep everything in motion and take the work to the man and not the man to the work. That is the real principle of our production, and

conveyors are only one of many means to an end"^[11]

The post-industrial economy was noted in 1973 by Daniel Bell.^[12] He stated that the future economy would provide more GDP and employment from services than from manufacturing and have a great effect on society. Since all sectors are highly interconnected, this did not reflect less importance for manufacturing, agriculture, and mining but just a shift in the type of economic activity.

Operations management

Although productivity benefited considerably from technological inventions and division of labor, the problem of systematic measurement of performances and the calculation of these by the use of formulas remained somewhat unexplored until

In 1911 Taylor published his "

1. The development of a true science;
2. The scientific selection of the
   worker
   ;
3. The scientific education and development of the worker;
4. Intimate friendly cooperation between the management and the workers.

Taylor is also credited for developing stopwatch

In 1913 Ford Whitman Harris published a paper on "How many parts to make at once", in which he presented the idea of the economic order quantity model. He described the problem as follows:

"

setup costs" on the job fix the minimum. Experience has shown one manager a way to determine the economical size of lots."^[18]

Harris described his theory as "reasonably correct", although "not rigorously accurate".[18] His paper inspired a large body of mathematical literature focusing on the problem of production planning and inventory control.^{[citation needed]}

In 1924

"For our present purpose a phenomenon will be said to be controlled when, through the use of past experience, we can predict, at least within

limits, how the phenomenon may be expected to vary in the future. Here it is understood that prediction within limits means that we can state, at least approximately, the probability that the observed phenomenon will fall within the given limits."^[19]

The methods-time measurement may be defined as follows:

Methods-time measurement is a procedure which analyzes any manual operation or method into the basic motions required to perform it and assigns to each motion a predetermined time standard which is determined by the nature of the motion and the conditions under which it is made.

Thus it may be seen that methods-time measurement is basically a tool of method analysis that gives answers in terms of time without the necessity of making stop-watch time studies.^[21]

Up to this point in history,

1. Process control: SPC and worker responsibility over quality
2. Easy able-to-see quality: boards, gauges, meters, etc. and poka-yoke
3. Insistence on compliance: "quality first"
4. Line stop: stop the line to correct quality problems
5. Correcting one's own errors: worker fixed a defective part if he produced it
6. The 100% check: automated inspection techniques and foolproof machines
7. Continual improvement: ideally zero defects.^[26]

Meanwhile, in the sixties, a different approach was developed by George W. Plossl and Oliver W. Wight,

Dramatic changes were occurring in the service industries as well. Beginning in 1955 McDonald's provided one of the first innovations in service operations. McDonald's is founded on the idea of the production-line approach to service.^[29] This requires a standard and limited menu, an assembly-line type of production process in the back-room, high customer service in the front-room with cleanliness, courtesy and fast service. While modeled after manufacturing in the production of the food in the back-room, the service in the front-room was defined and oriented to the customer. It was the McDonald's operations system of both production and service that made the difference. McDonald's also pioneered the idea of franchising this operation system to rapidly spread the business around the country and later the world.^[30]

FedEx in 1971 provided the first overnight delivery of packages in the U.S. This was based on the innovative idea of flying all packages into the single airport in Memphis Tenn by midnight each day, resorting the packages for delivery to destinations and then flying them back out the next morning for delivery to numerous locations. This concept of a fast package delivery system created a whole new industry, and eventually allowed fast delivery of online orders by Amazon and other retailers.^[31]

Walmart provided the first example of very low cost retailing through design of their stores and efficient management of their entire supply chain. Starting with a single store in Roger's Arkansas in 1962, Walmart has now become the world's largest company. This was accomplished by adhering to their system of delivering the goods and the service to the customers at the lowest possible cost. The operations system included careful selection of merchandise, low cost sourcing, ownership of transportation, cross-docking, efficient location of stores and friendly home-town service to the customer.^[32]

In 1987 the International Organization for Standardization (ISO), recognizing the growing importance of quality, issued the ISO 9000, a family of standards related to quality management systems. There standards apply to both manufacturing and service organizations. There has been some controversy regarding the proper procedures to follow and the amount of paperwork involved, but much of that has improved in current ISO 9000 revisions.

With the coming of the Internet, in 1994

• Business process re-engineering (launched by Michael Hammer in 1993^[34]): a business management strategy focusing on the analysis and design of workflows and business processes within an organization. BPR seeks to help companies radically restructure their organizations by focusing on the ground-up design of their business processes.
• Lean systems is a systemic method for the elimination of waste ("Muda") within a manufacturing or service process. Lean also takes into account waste created through overburden ("Muri") and waste created through unevenness in work loads ("Mura"). The term lean manufacturing was coined in the book The Machine that Changed the World.^[35] Subsequently, lean services has been widely applied.
• DFSS
  (for designing new products and new processes)
• Reconfigurable manufacturing system: a production system designed at the outset for rapid change in its structure, as well as its hardware and software components, in order to quickly adjust its production capacity and functionality within a part family in response to sudden market changes or intrinsic system change.
• Project production management: the application of the analytical tools and techniques developed for operations management, as described in Factory Physics to the activities within major capital projects such as encountered in oil and gas and civil infrastructure delivery.

Topics

Production systems

A production system comprises both the technological elements (machines and tools) and organizational behavior (division of labor and information flow). An individual production system is usually analyzed in the literature referring to a single business; therefore it is usually improper to include in a given production system the operations necessary to process goods that are obtained by purchasing or the operations carried by the customer on the sold products, the reason being simply that since businesses need to design their own production systems this then becomes the focus of analysis, modeling and decision making (also called "configuring" a production system).

A first possible distinction in production systems (technological classification) is between continuous process production and discrete part production (manufacturing).

• Process production means that the product undergoes physical-chemical transformations and lacks assembly operations, and therefore the original raw materials cannot easily be obtained from the final product. Examples include:
  petroleum products
  .
• Part production (e.g. cars and ovens) comprises both
  assembly lines and assembly shops (both manual and automated operations).^[36][37]

Another possible classification

Operations strategy concerns policies and plans of use of the firm productive resources with the aim of supporting long term competitive strategy. Metrics in operations management can be broadly classified into efficiency metrics and effectiveness metrics. Effectiveness metrics involve:

1. Price (actually fixed by marketing, but lower bounded by production cost): purchase price, use costs, maintenance costs, upgrade costs, disposal costs
2. Quality: specification and compliance
3. Time: productive lead time, information lead time, punctuality
4. Flexibility: mix (capacity to change the proportions between quantities produced in the system), volume (capacity to increase system output), gamma (capacity to expand the product family in the system)
5. Stock availability
6. Ecological Soundness: biological and environmental impacts of the system under study.

A more recent approach, introduced by Terry Hill,

ABC analysis is a method for analyzing inventory based on Pareto distribution, it posits that since revenue from items on inventory will be power law distributed then it makes sense to manage items differently based on their position on a revenue-inventory level matrix, 3 classes are constructed (A, B and C) from cumulative item revenues, so in a matrix each item will have a letter (A, B or C) assigned for revenue and inventory. This method posits that items away from the diagonal should be managed differently: items in the upper part are subject to risk of obsolescence, items in the lower part are subject to risk of stockout.

Overall equipment effectiveness (OEE) is defined as the product between system availability, cycle time efficiency and quality rate. OEE is typically used as key performance indicator (KPI) in conjunction with the lean manufacturing approach.

Configuration and management

Designing the configuration of production systems involves both

buffer stocks, the latter usually modeled as a function of demand variability. The economic production quantity^[43]

(EPQ) differs from the EOQ model only in that it assumes a constant fill rate for the part being produced, instead of the instantaneous refilling of the EOQ model.

workloads, rough-cut capacity planning, MPS, capacity requirements planning, traditional MRP planning, control (bottom) concerned with scheduling

.

purchase orders

and production orders (also called jobs).

The MPS can be seen as a kind of aggregate planning for production coming in two fundamentally opposing varieties: plans which try to chase demand and level plans which try to keep uniform capacity utilization. Many models have been proposed to solve MPS problems:

• Analytical models (e.g. Magee Boodman model)
• Exact optimization algorithmic models (e.g. LP and ILP)
• Heuristic models (e.g. Aucamp model).

MRP can be briefly described as a 3s procedure: sum (different orders), split (in lots), shift (in time according to item lead time). To avoid an "explosion" of data processing in MRP (number of BOMs required in input) planning bills (such as family bills or super bills) can be useful since they allow a rationalization of input data into common codes. MRP had some notorious problems such as infinite

MRP II, enterprise resource planning (ERP) and advanced planning and scheduling

(APS).

In this context problems of scheduling (sequencing of production), loading (tools to use), part type selection (parts to work on) and applications of operations research have a significant role to play.

just in time and autonomation (jidoka), all aimed at reducing waste (usually applied in PDCA style). Some additional elements are also fundamental:^[44]

production smoothing (Heijunka), capacity buffers, setup reduction, cross-training and plant layout.

• MPS and a final assembly schedule developed from the MPS by smoothing aggregate production requirements in smaller time buckets and sequencing final assembly to achieve repetitive manufacturing. If these conditions are met, expected throughput can be equaled to the inverse of takt time. Besides volume, heijunka also means attaining mixed-model production, which however may only be feasible through set-up reduction. A standard tool for achieving this is the Heijunka box
  .
• Capacity buffers: ideally a JIT system would work with zero breakdowns, this however is very hard to achieve in practice, nonetheless Toyota favors acquiring extra capacity over extra WIP to deal with starvation.
• Set-up
  reduction: typically necessary to achieve mixed-model production, a key distinction can be made between internal and external setup. Internal setups (e.g. removing a die) refers to tasks when the machine is not working, while external setups can be completed while the machine is running (ex:transporting dies).
• Cross training: important as an element of Autonomation, Toyota cross trained their employees through rotation, this served as an element of production flexibility, holistic thinking and reducing boredom.
• Layout: U-shaped lines or cells are common in the lean approach since they allow for minimum walking, greater worker efficiency and flexible capacity.

A series of tools have been developed mainly with the objective of replicating Toyota success: a very common implementation involves small cards known as

kanbans

; these also come in some varieties: reorder kanbans, alarm kanbans, triangular kanbans, etc. In the classic kanban procedure with one card:

• Parts are kept in containers with their respective kanbans
• The downstream station moves the kanban to the upstream station and starts producing the part at the downstream station
• The upstream operator takes the most urgent kanban from his list (compare to queue discipline from queue theory) and produces it and attach its respective kanban

The two-card kanban procedure differs a bit:

• The downstream operator takes the production kanban from his list
• If required parts are available he removes the move kanban and places them in another box, otherwise he chooses another production card
• He produces the part and attach its respective production kanban
• Periodically a mover picks up the move kanbans in upstream stations and search for the respective parts, when found he exchanges production kanbans for move kanbans and move the parts to downstream stations

Since the number of kanbans in the production system is set by managers as a constant number, the kanban procedure works as WIP controlling device, which for a given arrival rate, per Little's law, works as a lead time controlling device.

Value stream mapping, a representation of materials and information flows inside a company, mainly used in the lean manufacturing approach. The calculation of the time-line (bottom) usually involves using Little's law to derive lead time from stock levels and takt time

.

In Toyota the TPS represented more of a philosophy of production than a set of specific lean tools, the latter would include:

• SMED
  : a method for reducing changeover times
• Value stream mapping
  : a graphical method for analyzing the current state and designing a future state
• lot-size reduction
• elimination of time batching
• manufacturing cells
• single-point scheduling, the opposite of the traditional push approach
• multi-process handling: when one operator is responsible for operating several machines or processes
• poka-yoke: any mechanism in lean manufacturing that helps an equipment operator avoid (yokeru) mistakes (poka)
• 5S: describes how to organize a work space for efficiency and effectiveness by identifying and storing the items used, maintaining the area and items, and sustaining the new order
• backflush accounting: a product costing approach in which costing is delayed until goods are finished

Seen more broadly, JIT can include methods such as: product standardization and

vendor rating

(JIT production is very sensitive to replenishment conditions).

In heavily

deadlocks

, as these can lead to productivity losses.

Project production management (PPM) applies the concepts of operations management to the execution of delivery of capital projects by viewing the sequence of activities in a project as a production system.^[45][46] Operations managements principles of variability reduction and management are applied by buffering through a combination of capacity, time and inventory.

Service operations

Main article: Operations management for services

Service industries are a major part of economic activity and employment in all industrialized countries comprising 80 percent of employment and GDP in the U.S. Operations management of these services, as distinct from manufacturing, has been developing since the 1970s through publication of unique practices and academic research.^[47] Please note that this section does not particularly include "Professional Services Firms" and the professional services practiced from this expertise (specialized training and education within).

According to Fitzsimmons, Fitzsimmons and Bordoloi (2014) differences between manufactured goods and services are as follows:^[48]

• Simultaneous production and consumption. High contact services (e.g. health care) must be produced in the presence of the customer, since they are consumed as produced. As a result, services cannot be produced in one location and transported to another, like goods. Service operations are therefore highly dispersed geographically close to the customers. Furthermore, simultaneous production and consumption allows the possibility of self-service involving the customer at the point of consumption (e.g. gas stations). Only low-contact services produced in the "backroom" (e.g., check clearing) can be provided away from the customer.
• Perishable. Since services are perishable, they cannot be stored for later use. In manufacturing companies, inventory can be used to buffer supply and demand. Since buffering is not possible in services, highly variable demand must be met by operations or demand modified to meet supply.
• Ownership. In manufacturing, ownership is transferred to the customer. Ownership is not transferred for service. As a result, services cannot be owned or resold.
• Tangibility. A service is intangible making it difficult for a customer to evaluate the service in advance. In the case of a manufactured good, customers can see it and evaluate it. Assurance of quality service is often done by licensing, government regulation, and branding to assure customers they will receive a quality service.

These four comparisons indicate how management of service operations are quite different from manufacturing regarding such issues as capacity requirements (highly variable), quality assurance (hard to quantify), location of facilities (dispersed), and interaction with the customer during delivery of the service (product and process design).

While there are differences there are also many similarities. For example, quality management approaches used in manufacturing such as the Baldrige Award, and Six Sigma have been widely applied to services. Likewise, lean service principles and practices have also been applied in service operations. The important difference being the customer is in the system while the service is being provided and needs to be considered when applying these practices.^[49]

One important difference is service recovery. When an error occurs in service delivery, the recovery must be delivered on the spot by the service provider. If a waiter in a restaurant spills soup on the customer's lap, then the recovery could include a free meal and a promise of free dry cleaning. Another difference is in planning capacity. Since the product cannot be stored, the service facility must be managed to peak demand which requires more flexibility than manufacturing. Location of facilities must be near the customers and scale economics can be lacking. Scheduling must consider the customer can be waiting in line. Queuing theory has been devised to assist in design of service facilities waiting lines. Revenue management is important for service operations, since empty seats on an airplane are lost revenue when the plane departs and cannot be stored for future use.^[50]

Mathematical modeling

equilibrium distribution

of the network.

optimal solution

.

There are also fields of mathematical theory which have found applications in the field of operations management such as

multivariate calculus and linear algebra. Queue theory is based on Markov chains and stochastic processes.^[51] Computations of safety stocks are usually based on modeling demand as a normal distribution and MRP and some inventory problems can be formulated using optimal control.^[52]

When analytical models are not enough, managers may resort to using

discrete event simulation paradigm, where the simulation model possesses a state which can only change when a discrete event happens, which consists of a clock and list of events. The more recent transaction-level modeling

paradigm consists of a set of resources and a set of transactions: transactions move through a network of resources (nodes) according to a code, called a process.

sample an upper control line and lower control line are fixed. When the statistic moves out of bounds, an alarm is given and possible causes are investigated. In this drawing the statistic of choice is the mean

and red points represent alarm points.

Since real production processes are always affected by disturbances in both inputs and outputs, many companies implement some form of

Seven Basic Tools of Quality

designation provides a summary of commonly used tools:

• check sheets
• Pareto charts
• Ishikawa diagrams
  (Cause-and-effect diagram)
• control charts
• histogram
• scatter diagram
• stratification

These are used in approaches like total quality management and Six Sigma. Keeping quality under control is relevant to both increasing customer satisfaction and reducing processing waste.

Operations management

forecast errors. Demand forecasting is also a critical part of push systems, since order releases have to be planned ahead of actual clients’ orders. Also, any serious discussion of capacity planning

involves adjusting company outputs with market demands.

Safety, risk and maintenance

Other important

safety management systems (see also safety engineering and Risk management), facility management

and supply chain integration.

Organizations

The following organizations support and promote operations management:

• Association for Operations Management
  (APICS) which supports the Production and Inventory Management Journal
• European Operations Management Association (EurOMA) which supports the International Journal of Operations & Production Management
• Production and Operations Management Society (POMS) which supports the journal: Production and Operations Management
• Institute for Operations Research and the Management Sciences (INFORMS)
• The Manufacturing and Service Operations Management Society (MSOM) of INFORMS which supports the journal: Manufacturing & Service Operations Management
• Institute of Operations Management (UK)
• Association of Technology, Management, and Applied Engineering (ATMAE)

Journals

The following high-ranked^[54] academic journals are concerned with operations management issues:

• Management Science
• Manufacturing & Service Operations Management
• Operations Research
• International Journal of Operations & Production Management
• Production and Operations Management
• Transportation Research – Part E
• Journal of Operations Management
• European Journal of Operational Research
• Annals of Operations Research

See also

• Association for Supply Chain Management (APICS)
• Benchmarking
• Business process management
• Business process mapping
• Cause-and-effect analysis
• Change management
• Customer benefit package
• Failure mode and effects analysis
• Industrial technology
• Inventory management software
• Line management
• National Institute of Industrial Engineering
• Performance metrics
• Project management
• Project production management
• Requirements engineering
• Risk management
• Root cause analysis
• Silver–Meal heuristic
• Work breakdown structure

References

1. ^ OperationsAcademia.org: The state-of-the-art of PhD research in Operations Research/Management Science and related disciplines Retrieved on October 22, 2016
2. ^ Great Operations: What is Operations Management Archived 2016-10-07 at the Wayback Machine Retrieved on July 3, 2013
3. ^
   R. B. Chase
   , F.R. Jacobs, N. Aquilano, Operations Management: For Competitive Advantage, McGraw-Hill 2007
4. ISBN 978-0-13-280739-5
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7. ^ Friedrick Klemm, A history of Western Technology, Charles Scribner's Sons 1959 in D. A. Wren and A. G. Bedeian, The Evolution of Management Thought, Wiley 2009
8. Cyropedia
   , Book VIII, Delphi Classics
9. A. G. Bedeian
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10. ^ Fisk, Donald M. (2003-01-30). "American Labor in the 20th Century" (PDF).
11. ^ Henry Ford, Today and Tomorrow, New York, 1926
12. ISBN 978-0465012817
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13. ^ Taylor, Frederick Winslow (1896), A Piece Rate System, read before the American Society of Mechanical Engineers http://wps.prenhall.com/wps/media/objects/107/109902/ch17_a3_d2.pdf
14. Taylor, F. W.
    , On the Art of Cutting Metals, American Society of Mechanical Engineers (1906)
15. Taylor, F. W., Shop Management (1903), a handbook read before the American Society of mechanical engineers, New York (this has been republished in 1911 https://archive.org/details/shopmanagement00taylgoog
    )
16. Taylor, Frederick Winslow
    (1911), The Principles of Scientific Management. New York, NY, US and London, UK: Harper & Brothers. LCCN 11010339. OCLC 233134. Also available from Project Gutenberg.
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18. ^
    JSTOR 170962
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19. ^
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20. ^ ^{a b} D.C. Montgomery, Statistical Quality Control: A Modern Introduction, 7th edition 2012
21. ^ H.B. Maynard, J.L. Schwab, G.J. Stegemerten, Methods Time Measurement, McGraw-Hill 1948 http://www.library.wisc.edu/selectedtocs/ca1794.pdf
22. ^ L. V. Kantorovich, Mathematical Methods of Organizing and Planning Production, Management Science 1960 [English translation from 1939]
23. ^ Taiichi Ohno, Toyota Production System, Productivity Pres 1988
24. ^ J. N. Edwards, MRP and Kanban-American style, APICS 26th Conference Proceedings, pp. 586–603 1983
25. OCLC 250573852
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26. ^ R. J. Schnonberger, Japanese Manufacturing Techniques: Nine Hidden Lessons in Simplicity, New York 1982
27. ^ ^{a b} R.B. Grubbström, Modelling production opportunities – an historical overview, Int. J. Production Economics 1995
28. ^ Orlickly, Materials Requirement Planning, McGraw-Hill 1975
29. ^ Levitt, Theodore (1972). "The Production-Line Approach to Services". Harvard Business Review. 50 (4): 41–52.
30. ISBN 0-553-34759-4
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31. ^ Birla, Madan (2007). FedEx Delivers. New York: Wiley.
32. ^ Fishman, Charles (2006). Wal-Mart Effect. New York: Penguin Books.
33. ^ "14 Quirky Things You Didn't Know About Amazon". Business Insider.
34. ^ M.Hammer, J.Champy, Reengineering the Corporation: A Manifesto for Business Revolution, Harper Business 1993
35. ^ Womack, Jones, Roos, The Machine that Changed the World, Free Press, 1990
36. ^ ^{a b} A. Portioli, A.Pozzetti, Progettazione dei sistemi produttivi, Hoepli 2003
37. ^ Note: this classification is very old but it has been subject to update as production systems have evolved over the 20th century, for a complete picture consult recent texts
38. ^ J.C. Wortmann, Chapter: "A classification scheme for master production schedule", in Efficiency of Manufacturing Systems, C. Berg, D. French and B. Wilson (eds) New York, Plenum Press 1983
39. ^ Roger W. Schmenner, How Can Service Businesses Survive and Prosper?, Sloan Management Review, vol. 27, no. 3, Spring 1986 http://umairbali.ekalaam.com/Business%20Process%20Workflow%20Analysis/Week6/SMR-ServiceBusiness.pdf Archived 2013-11-13 at the Wayback Machine
40. ^ "How blue jeans is made – material, manufacture, making, history, used, procedure, steps, product, machine". madehow.com.
41. ^ T. Hill, Manufacturing Strategy-Text and Cases, 3rd ed. Mc-Graw Hill 2000
42. ^ Grando A., Organizzazione e Gestione della Produzione Industriale, Egea 1993
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44. ^ W. Hopp, M. Spearman, Factory Physics, 3rd ed. Waveland Press, 2011
45. ^ "Factory Physics for Managers", E. S. Pound, J. H. Bell, and M. L. Spearman, McGraw-Hill, 2014, p 47    
46. ^ "New Era of Project Delivery – Project as Production System", R. G. Shenoy and T. R. Zabelle, Journal of Project Production Management, Vol 1,  pp Nov 2016, pp 13–24 https://www.researchgate.net/publication/312602707_New_Era_of_Project_Delivery_-_Project_as_Production_System
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50. ISBN 978-0-273-74048-3
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51. ^ Burnetas A.N. and M. N.Katehakis (1993).. "On Sequencing Two Types of Tasks on a Single Processor under Incomplete Information", Probability in the Engineering and Informational Sciences, 7 (1), 85–0119.
52. ISBN 0-256-11379-3
53. ^ Katehakis M.N. and C. Derman (1989). "On the maintenance of systems composed of highly reliable components", Management Science, 6 (5): 16–28.
54. ^ "Rankings" (PDF). Archived from the original (PDF) on 2013-05-27. Retrieved 2012-07-17.

Further reading

• Daniel Wren, The Evolution of Management Thought, 3rd edition, New York Wiley 1987.
• W. Hopp, M. Spearman, Factory Physics, 3rd ed. Waveland Press, 2011 online (Part 1 contains both description and critical evaluation of the historical development of the field).
• R. B. Chase, F. R. Jacobs, N. J.Aquilano, Operations Management for Competitive Advantage, 11th edition, McGraw-Hill, 2007.
• Askin, R. G., C.R. Standridge, Modeling & Analysis Of Manufacturing Systems, John Wiley and Sons, New York 1993.
• J. A. Buzacott, J. G. Shanthikumar, Stochastic models of manufacturing systems, Prentice Hall, 1993.
• D. C. Montgomery, Statistical Quality Control: A Modern Introduction, 7th edition, 2012.
• R. G. Poluha: The Quintessence of Supply Chain Management: What You Really Need to Know to Manage Your Processes in Procurement, Manufacturing, Warehousing and Logistics (Quintessence Series). First Edition. Springer Heidelberg New York Dordrecht London 2016.
  ISBN 978-3662485132
  .