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Operations management is concerned with designing and controlling theproduction ofgoods andservices,[1] ensuring thatbusinesses areefficient in using resources to meetcustomer requirements.
It is concerned with managing an entire production system that converts inputs (in the forms ofraw materials,labor,consumables, andenergy) 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 anorganization along withsupply chains,marketing,finance andhuman 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 andinventory 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]
The history of production and operation systems begins around 5000 B.C. whenSumerian priests developed the ancient system of recording inventories, loans, taxes, and business transactions. The next major historical application of operation systems occurred in 4000 B.C., when theEgyptians started usingplanning,organization, andcontrol in largeprojects such as the construction of the pyramids. By 1100 B.C., labor was being specialized inChina; by about 370 B.C.,Xenophon described the advantages of dividing the various operations necessary for the production of shoes among different individuals inancient Greece:[7][8]
"...In large cities, on the other hand, inasmuch as many people have demands to make upon each branch of industry, one trade alone, and very often even less than a whole trade, is enough to support a man: one man, for instance, makes shoes for men, and another for women; and there are places even where one man earns a living by only stitching shoes, another by cutting them out, another by sewing the uppers together, while there is another who performs none of these operations but only assembles the parts. It follows, therefore, as a matter of course, that he who devotes himself to a very highly specialized line of work is bound to do it in the best possible manner."
In theMiddle Ages, kings and queens ruled over large areas of land. Loyal noblemen maintained large sections of the monarch's territory. This hierarchical organization in which people were divided into classes based on social position and wealth became known as thefeudal system. In the feudal system,vassals andserfs produced for themselves and people of higher classes by using the ruler's land and resources. Although a large part of labor was employed in agriculture,artisans contributed to economic output and formedguilds. The guild system, operating mainly between 1100 and 1500, consisted of two types: merchant guilds, who bought and sold goods, and craft guilds, which made goods. Although guilds were regulated as to the quality of work performed, the resulting system was rather rigid,shoemakers, for example, were prohibited from tanning hides.[9]
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]
TheIndustrial Revolution was facilitated by two elements: interchangeability of parts and division of labor.Division of labor has been a feature from the beginning ofcivilization, the extent to which the division is carried out varied considerably depending on period and location. Compared to the Middle Ages, theRenaissance and theAge of Discovery were characterized by a greater specialization in labor, which was a characteristic of the growing cities and trade networks of Europe. An important leap in manufacturing efficiency came in the late eighteenth century asEli Whitney popularized the concept ofinterchangeability of parts when he manufactured 10,000 muskets. Up to this point in the history of manufacturing, each product (e.g. each musket) was considered a special order, meaning that parts of a given musket were fitted only for that particular musket and could not be used in other muskets. Interchangeability of parts allowed the mass production of parts independent of the final products in which they would be used. An entire new market to fill the need for the sale and manufacturing of muskets began at this time.[citation needed]
In 1883,Frederick Winslow Taylor introduced thestopwatch method for accurately measuring the time to perform each single task of a complicated job. He developed the scientific study of productivity and identifying how to coordinate different tasks to eliminate wasting of time and increase the quality of work. The next generation of scientific study occurred with the development ofwork sampling andpredetermined motion time systems (PMTS). Work sampling is used to measure the random variable associated with the time of each task. PMTS allows the use of standard predetermined tables of the smallest body movements (e.g. turning the left wrist by 90°), and integrating them to predict the time needed to perform a simple task. PMTS has gained substantial importance due to the fact that it can predict work measurements without observing the actual work. The foundation of PMTS was laid out by the research and development ofFrank B. andLillian M. Gilbreth around 1912. The Gilbreths took advantage of taking motion pictures at known time intervals while operators were performing the given task.[citation needed]
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 theproduction line has been used multiple times in history prior to Henry Ford: theVenetian Arsenal (1104); Smith's pin manufacturing, in theWealth of Nations (1776) or Brunel'sPortsmouth Block Mills (1802).Ransom Olds was the first to manufacture cars using the assembly line system, butHenry Ford developed the first auto assembly system where a car chassis was moved through the assembly line by aconveyor belt while workers added components to it until the car was completed. DuringWorld War II, the growth of computing power led to further development of efficient manufacturing methods and the use of advanced mathematical and statistical tools. This was supported by the development of academic programs inindustrial andsystems engineering disciplines, as well as fields of operations research and management science (as multi-disciplinary fields of problem solving). While systems engineering concentrated on the broad characteristics of the relationships between inputs and outputs of generic systems, operations researchers concentrated on solving specific and focused problems. The synergy ofoperations research and systems engineering allowed for the realization of solving large scale and complex problems in the modern era. Recently, the development of faster and smaller computers,intelligent systems, and theWorld Wide Web has opened new opportunities for operations, manufacturing, production, and service systems.[citation needed]
Before theFirst Industrial Revolution, work was mainly done through two systems:domestic system andcraft guilds. In the domestic systemmerchants took materials to homes where artisans performed the necessary work, craft guilds on the other hand were associations ofartisans which passed work from one shop to another, for example: leather was tanned by atanner, passed tocurriers, and finally arrived atshoemakers andsaddlers.
The beginning of the industrial revolution is usually associated with the eighteenth-century Englishtextile industry, with the invention of theflying shuttle byJohn Kay in 1733, thespinning jenny byJames Hargreaves in 1765, thewater frame byRichard Arkwright in 1769 and thesteam engine byJames Watt in 1765. In 1851 at theCrystal Palace Exhibition the termAmerican system of manufacturing was used to describe the new approach that was evolving in theUnited States of America which was based on two central features:interchangeable parts and extensive use ofmechanization to produce them.
Henry Ford was 39 years old when he founded theFord Motor Company in 1903, with $28,000 capital from twelve investors. Themodel T car was introduced in 1908, however it was not until Ford implemented the assembly line concept, that his vision of making a popular car affordable by every middle-class American citizen would be realized. The first factory in whichHenry Ford used the concept of theassembly line wasHighland Park (1913), he characterized the system as follows:
"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, andconveyors are only one of many means to an end"[11]
This became one of the central ideas that led tomass production, one of the main elements of theSecond Industrial Revolution, along with emergence of theelectrical industry andpetroleum industry.
Thepost-industrial economy was noted in 1973 by Daniel Bell.[12] He stated that the future economy would provide moreGDP 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.
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 untilFrederick Taylor, whose early work focused on developing what he called a "differential piece-rate system"[13] and a series of experiments, measurements and formulas dealing withcutting metals[14] and manual labor.[15] The differentialpiece-rate system consisted in offering two different pay rates for doing a job: a higher rate for workers with high productivity (efficiency) and who produced high quality goods (effectiveness) and a lower rate for those who fail to achieve the standard. One of the problems Taylor believed could be solved with this system was the problem ofsoldiering: faster workers reducing their production rate to that of the slowest worker.
In 1911 Taylor published his "The Principles of Scientific Management",[16] in which he characterizedscientific management (also known asTaylorism) as:
Taylor is also credited for developing stopwatchtime study. This, combined withFrank andLillian Gilbrethmotion study, gave way totime and motion study, which is centered on the concepts of standard method andstandard time. Frank Gilbreth is also responsible for introducing theflow process chart in 1921.[17] Other contemporaries of Taylor worth remembering areMorris Cooke (rural electrification in the 1920s and implementer of Taylor's principles of scientific management in the Philadelphia's Department of Public Works),Carl Barth (speed-and-feed-calculating slide rules) andHenry Gantt (Gantt chart). Also in 1910Hugo Diemer published the firstindustrial engineering book:Factory Organization and Administration.
In 1913Ford Whitman Harris published a paper on "How many parts to make at once", in which he presented the idea of theeconomic order quantity model. He described the problem as follows:
"Interest on capital tied up inwages, material andoverhead sets a maximum limit to the quantity of parts which can be profitably manufactured at one time; "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 ofmathematical literature focusing on the problem ofproduction planning andinventory control.[citation needed]
In 1924Walter Shewhart introduced thecontrol chart through a technical memorandum while working atBell Labs, central to his method was the distinction betweencommon cause and special cause of variation. In 1931 Shewhart published his Economic Control of Quality of Manufactured Product,[19] the first systematic treatment[20] of the subject ofstatistical process control (SPC). He defined control:
"For our present purpose a phenomenon will be said to be controlled when, through the use of past experience, we can predict, at least withinlimits, 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, theprobability that the observed phenomenon will fall within the given limits."[19]
In the 1940smethods-time measurement (MTM) was developed byH.B. Maynard, J.L. Schwab and G.J. Stegemerten. MTM was the first of a series ofpredetermined motion time systems, predetermined in the sense that estimates of time are not determined in loco but are derived from an industry standard. This was explained by its originators in a book they published in 1948 calledMethods-Time Measurement.
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 eachmotion 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,optimization techniques were known for a very long time, from the simple methods employed by Harris to the more elaborate techniques of thecalculus of variations developed byEuler in 1733 or themultipliers employed byLagrange in 1811, andcomputers were slowly being developed, first asanalog computers bySir William Thomson (1872) andJames Thomson (1876) moving to the electromechanical computers ofKonrad Zuse (1939 and 1941). DuringWorld War II however, the development ofmathematical optimization went through a major boost with the development of theColossus computer, the first electronic digital computer that was all programmable, and the possibility to computationally solve largelinear programming problems, first byKantorovich[22] in 1939 working for theSoviet government and later in 1947 with thesimplex method ofDantzig. These methods are known today as belonging to the field ofoperations research.
From this point on, a curious development took place: while in the United States the possibility of applying the computer to business operations led to the development of management software architecture such asMRP and successive modifications, and ever more sophisticated optimization techniques andmanufacturing simulation software, in post-war Japan a series of events at Toyota Motor led to the development of theToyota Production System (TPS) andlean manufacturing.
In 1943, in Japan,Taiichi Ohno arrived atToyota. Toyota evolved a unique manufacturing system centered on two complementary notions:just in time (produce only what is needed) andautonomation (automation with a human touch). Regarding JIT, Ohno was inspired by Americansupermarkets:[23] workstations functioned like a supermarket shelf where the customer can get products they need, at the time they need and in the amount needed, the workstation (shelf) is then restocked. Autonomation was developed bySakichi Toyoda in Toyoda Spinning and Weaving: an automatically activated loom that was also foolproof, that is automatically detected problems. In 1983 J.N Edwards published his "MRP and Kanban-American style" in which he described JIT goals in terms of seven zeros:[24] zero defects, zero (excess) lot size, zero setups, zero breakdowns, zero handling, zero lead time and zero surging. This period also marks the spread oftotal quality management (TQM) in Japan, ideas initially developed by American authors such asDeming,Juran andArmand V. Feigenbaum.[25] TQM is a strategy for implementing and managing quality improvement on an organizational basis, this includes: participation, work culture, customer focus, supplier quality improvement and integration of the quality system with business goals.[20] Schnonberger identified seven fundamentals principles essential to the Japanese approach:
Meanwhile, in the sixties, a different approach was developed by George W. Plossl and Oliver W. Wight,[27] this approach was continued by Joseph Orlicky as a response to the TOYOTA Manufacturing Program which led tomaterial requirements planning (MRP) atIBM, latter gaining momentum in 1972 when the American Production and Inventory Control Society launched the "MRP Crusade". One of the key insights of this management system was the distinction betweendependent demand andindependent demand. Independent demand is demand which originates outside of the production system, therefore not directly controllable, and dependent demand is demand for components of final products, therefore subject to being directly controllable by management through thebill of materials, viaproduct design. Orlicky wrote "Materials Requirement Planning" in 1975,[28] the first hard cover book on the subject.[27]MRP II was developed by Gene Thomas at IBM, and expanded the original MRP software to include additional production functions.Enterprise resource planning (ERP) is the modern software architecture, which addresses, besides production operations,distribution,accounting,human resources andprocurement.
Dramatic changes were occurring in the service industries as well. Beginning in 1955McDonald'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 theInternational Organization for Standardization (ISO), recognizing the growing importance of quality, issued theISO 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 1994Amazon devised a service system of on-line retailing and distribution. With this innovative system customers were able to search for products they might like to buy, enter the order for the product, pay online, and track delivery of the product to their location, all in two days. This required not only very large computer operations, but dispersed warehouses, and an efficient transportation system. Service to customers including a high merchandise assortment, return services of purchases, and fast delivery is at the forefront of this business.[33] It is the customer being in the system during the production and delivery of the service that distinguishes all services from manufacturing.
Recent trends in the field revolve around concepts such as:
A production system comprises both technological elements (machines and tools) andorganizational behavior (division of labor andinformation flow) needed to produce goods and services.[36] 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 bypurchasing or the operations carried by thecustomer on the sold products, the reason being simply that since businesses need to design their own production systems this then becomes the focus ofanalysis,modeling anddecision making (also called "configuring" a production system).[clarification needed]
A first possible distinction in production systems (technological classification) is between continuous process production and discrete part production (manufacturing).
Another possible classification[39] is one based onlead time (manufacturing lead time vs delivery lead time):engineer to order (ETO),purchase to order (PTO),make to order (MTO),assemble to order (ATO) andmake to stock (MTS). According to this classification different kinds of systems will have different customer order decoupling points (CODP), meaning thatwork in progress (WIP) cycle stock levels are practically nonexistent regarding operations located after the CODP (except forWIP due to queues). (SeeOrder fulfillment.)
The concept of production systems can be expanded to theservice sector world keeping in mind that services have some fundamental differences in respect to material goods: intangibility, client always present during transformation processes, no stocks for "finished goods". Services can be classified according to a service process matrix:[40] degree of labor intensity (volume) vs degree of customization (variety). With a high degree of labor intensity there are mass services (e.g.,commercial banking bill payments andstate schools) and professional services (e.g., personalphysicians andlawyers), while with a low degree of labor intensity there are service factories (e.g.,airlines andhotels) and service shops (e.g.,hospitals andauto mechanics).
The systems described above areideal types: real systems may present themselves as hybrids of those categories. Consider, for example, that the production ofjeans involves initiallycarding,spinning,dyeing andweaving, then cutting the fabric in different shapes and assembling the parts in pants or jackets by combining the fabric with thread, zippers and buttons, finallyfinishing anddistressing the pants/jackets before being shipped to stores.[41] The beginning can be seen as process production, the middle as part production and the end again as process production: it is unlikely that a single company will keep all the stages of production under a single roof, therefore the problem ofvertical integration andoutsourcing arises. Most products require,from asupply chain perspective, both process production and part production.
If a production system is concerned with theproduction of goods and services, an operations system is concerned withprovisioning them.[36] Not all management models distinguish between production and operations systems.[citation needed] When the two are distinguished, operations systems account for many of the tertiary factors that are abstracted away from in production system frameworks. In particular, there is an emphasis on service-based factors.
Operational systems generally fall into two main categories: service-based and manufacturing-based.
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.[42] 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:[43]
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, andSix 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.[44]
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.[45]
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 intoefficiency metrics andeffectiveness metrics. Effectiveness metrics involve:
A more recent approach, introduced by Terry Hill,[46] involves distinguishing competitive variables in order winner and order qualifiers when defining operations strategy. Order winners are variables which permit differentiating the company from competitors, while order qualifiers are prerequisites for engaging in a transaction. This view can be seen as a unifying approach between operations management andmarketing (seesegmentation andpositioning).
Productivity is a standard efficiency metric for evaluation of production systems, broadly speaking a ratio between outputs and inputs, and can assume many specific forms,[47] for example: machine productivity, workforce productivity, raw material productivity, warehouse productivity (=inventory turnover). It is also useful to break up productivity in use U (productive percentage of total time) and yield η (ratio between produced volume and productive time) to better evaluate production systems performances. Cycle times can be modeled throughmanufacturing engineering if the individual operations are heavily automated, if the manual component is the prevalent one, methods used include:time and motion study,predetermined motion time systems andwork sampling.
ABC analysis is a method for analyzing inventory based onPareto distribution, it posits that since revenue from items on inventory will bepower 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 ofstockout.
Throughput is a variable which quantifies the number of parts produced in the unit of time. Although estimating throughput for a single process maybe fairly simple, doing so for an entire production system involves an additional difficulty due to the presence of queues which can come from: machinebreakdowns, processing time variability, scraps, setups,maintenance time, lack of orders, lack of materials,strikes, bad coordination between resources, mix variability, plus all these inefficiencies tend to compound depending on the nature of the production system. One important example of how system throughput is tied to system design arebottlenecks: in job shops bottlenecks are typically dynamic and dependent on scheduling while on transfer lines it makes sense to speak of "the bottleneck" since it can be univocally associated with a specific station on the line. This leads to the problem of how to definecapacity measures, that is an estimation of the maximum output of a given production system, andcapacity utilization.
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.
Designing theconfiguration of production systems involves bothtechnological andorganizational variables. Choices in production technology involve: dimensioningcapacity, fractioning capacity, capacity location,outsourcing processes, process technology,automation of operations, trade-off between volume and variety (seeHayes-Wheelwright matrix). Choices in the organizational area involve: defining workerskills andresponsibilities, team coordination, worker incentives and information flow.
Inproduction planning, there is a basic distinction between thepush approach and thepull approach, with the later including the singular approach ofjust in time. Pull means that the production system authorizes production based on inventory level; push means that production occurs based on demand (forecasted or present, that ispurchase orders). An individual production system can be both push and pull; for example activities before the CODP may work under a pull system, while activities after the CODP may work under a push system.
The traditional pull approach toinventory control, a number of techniques have been developed based on the work of Ford W. Harris[18] (1913), which came to be known as theeconomic order quantity (EOQ) model. This model marks the beginning ofinventory theory, which includes theWagner-Within procedure, thenewsvendor model,base stock model and thefixed time period model. These models usually involve the calculation ofcycle stocks andbuffer stocks, the latter usually modeled as a function of demand variability. The economic production quantity[48] (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.
Joseph Orlickly and others at IBM developed apush approach to inventory control and production planning, now known asmaterial requirements planning (MRP), which takes as input both themaster production schedule (MPS) and thebill of materials (BOM) and gives as output a schedule for the materials (components) needed in the production process. MRP therefore is a planning tool to managepurchase 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 tochase demand andlevel plans which try to keep uniform capacity utilization. Many models have been proposed to solve MPS problems:
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 infinitecapacity and fixedlead times, which influenced successive modifications of the original software architecture in the form ofMRP II,enterprise resource planning (ERP) andadvanced planning and scheduling (APS).
In this context problems ofscheduling (sequencing of production), loading (tools to use), part type selection (parts to work on) and applications ofoperations research have a significant role to play.
Lean manufacturing is an approach to production which arose inToyota between the end of World War II and the seventies. It comes mainly from the ideas ofTaiichi Ohno andSakichi Toyoda which are centered on the complementary notions ofjust in time andautonomation (jidoka), all aimed at reducing waste (usually applied inPDCA style). Some additional elements are also fundamental:[49] production smoothing (Heijunka), capacity buffers, setup reduction, cross-training and plant layout.
A series of tools have been developed mainly with the objective of replicating Toyota success: a very common implementation involves small cards known askanbans; these also come in some varieties: reorder kanbans, alarm kanbans, triangular kanbans, etc. In the classic kanban procedure with one card:
The two-card kanban procedure differs a bit:
Since the number of kanbans in the production system is set by managers as a constant number, the kanban procedure works asWIP controlling device, which for a given arrival rate, perLittle's law, works as a lead time controlling device.
In Toyota the TPS represented more of a philosophy of production than a set of specific lean tools, the latter would include:
Seen more broadly, JIT can include methods such as: product standardization andmodularity,group technology,total productive maintenance,job enlargement,job enrichment,flat organization andvendor rating (JIT production is very sensitive to replenishment conditions).
In heavilyautomated production systems production planning and information gathering may be executed via thecontrol system, attention should be paid however to avoid problems such asdeadlocks, 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.[50][51] Operations managements principles of variability reduction and management are applied by buffering through a combination of capacity, time and inventory.
There are also fields of mathematical theory which have found applications in the field of operations management such asoperations research: mainlymathematical optimization problems andqueue theory. Queue theory is employed in modelling queue and processing times in production systems while mathematical optimization draws heavily frommultivariate calculus andlinear algebra. Queue theory is based onMarkov chains andstochastic processes.[52] Computations ofsafety stocks are usually based on modeling demand as anormal distribution and MRP and some inventory problems can be formulated usingoptimal control.[53]
When analytical models are not enough, managers may resort to usingsimulation. Simulation has been traditionally done through thediscrete 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 recenttransaction-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.
Since real production processes are always affected by disturbances in both inputs and outputs, many companies implement some form ofquality management orquality control. TheSeven Basic Tools of Quality designation provides a summary of commonly used tools:
These are used in approaches liketotal quality management andSix Sigma. Keeping quality under control is relevant to both increasing customer satisfaction and reducing processing waste.
Operations managementtextbooks usually coverdemand forecasting, even though it is not strictly speaking an operations problem, because demand is related to some production systems variables. For example, a classic approach in dimensioningsafety stocks requires calculating thestandard deviation offorecast 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 ofcapacity planning involves adjusting company outputs with market demands.
Other importantmanagement problems involvemaintenance policies[54] (see alsoreliability engineering andmaintenance philosophy),safety management systems (see alsosafety engineering andrisk management),facility management andsupply chain integration.
The following organizations support and promote operations management:
The following high-ranked[55] academic journals are concerned with operations management issues:
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