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.Operations management is an area of concerned with designing and controlling the process of and redesigning in the production of. It involves the responsibility of ensuring that operations are in terms of using as few resources as needed and in terms of meeting customer requirements. Operations management is primarily concerned with planning, organizing and supervising in the contexts of production, manufacturing or the provision of services.It is concerned with managing an entire production system which is the process that converts inputs (in the forms of, and ) into outputs (in the form of goods and/or services), or delivers a product or services. Operations produce products, manage quality and creates service. Operation management covers sectors like banking systems, hospitals, companies, working with suppliers, customers, and using technology.

1. Project Management Mba Program

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. Ford Motor car assembly line: the classical example of a manufacturing production system.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. Contents.History The history of production and operation systems began around 5000 B.C. When 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. It was during this time that the started using, and in large such as the construction of the pyramids. 1568In the, 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 the. In the feudal system, and 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, contributed to economic output and formed. 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, for example, were prohibited from tanning hides.Services were also performed in the Middle Ages by servants. They provided service to the nobility for cooking, cleaning and entertainment.

Court jesters were service providers. The medieval army could also be considered a service since they defended the nobility.The was facilitated by two elements: interchangeability of parts and division of labor. Has always been a feature from the beginning of, the extent to which the division is carried out varied considerably depending on period and location. Compared to the Middle Ages, the and the were characterized by a greater specialization in labor, one of the characteristics of growing European cities and trade. It was in the late eighteenth century that popularized the concept of 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.In 1883, introduced the 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 of and (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 of and around 1912.

The Gilbreths took advantage of taking motion pictures at known time intervals while operators were performing the given task.Service Industries: 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. In 1900 had 31% employment in services, 31% in manufacturing and 38% in agriculture.The idea of the has been used multiple times in history prior to Henry Ford: the (1104); Smith's pin manufacturing, in the (1776) or Brunel's (1802).

Was the first to manufacture cars using the assembly line system, but developed the first auto assembly system where a car chassis was moved through the assembly line by a while workers added components to it until the car was completed. During World 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 in and disciplines, as well as fields of operations research and management science (as multi-disciplinary fields of problem solving). While 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 of 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, and the has opened new opportunities for operations, manufacturing, production, and service systems.Industrial Revolution. See also: andBefore the work was mainly done through two systems:.

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Flexible Manufacturing System: in the middle there are two rails for the shuttle to move between machining centers (there are also FMS which use ), in front of each machining center there is a buffer and in left we have a shelf for storing pallets. Usually in the back there is a similar system for managing the set of required for different operations.A production system comprises both the technological elements (machines and tools) and organizational behavior (division of labor and information flow). Delivery lead time is the blue bar, manufacturing time is the whole bar, the green bar is the difference between the two.Another possible classification is one based on (manufacturing lead time vs delivery lead time): (ETO), (PTO), (MTO), (ATO) and (MTS). According to this classification different kinds of systems will have different customer order decoupling points (CODP), meaning that (WIP) cycle stock levels are practically nonexistent regarding operations located after the CODP (except for due to queues). (See )The concept of production systems can be expanded to the 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: degree of labor intensity (volume) vs degree of customization (variety). With a high degree of labor intensity there are Mass Services (e.g., bill payments and ) and Professional Services (e.g., personal and ), while with a low degree of labor intensity there are Service Factories (e.g., and ) and Service Shops (e.g., and ).The systems described above are: real systems may present themselves as hybrids of those categories.

Consider, for example, that the production of involves initially, and, then cutting the fabric in different shapes and assembling the parts in pants or jackets by combining the fabric with thread, zippers and buttons, finally and the pants/jackets before being shipped to stores. The beginning can be seen as process production, the middle as part production and the end again as process production: it's unlikely that a single company will keep all the stages of production under a single roof, therefore the problem of and arises. Most products require, from a perspective, both process production and part production.Metrics: efficiency and effectiveness 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 metrics and metrics. Effectiveness metrics involve:.

(actually fixed by marketing, but lower bounded by production cost): purchase price, use costs, maintenance costs, upgrade costs, disposal costs.: specification and compliance.: productive, information lead time,.: mix, volume, gamma. Stock. Ecological Soundness: biological and of the system under study.A more recent approach, introduced by Terry Hill, 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 and (see and ).is a standard efficiency metric for evaluation of production systems, broadly speaking a ratio between outputs and inputs, and can assume many specific forms, for example: machine productivity, workforce productivity, raw material productivity, warehouse productivity (=). 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 through engineering if the individual operations are heavily automated, if the manual component is the prevalent one, methods used include:,. An ABC cumulated curve. Typically one curve is constructed for revenue (consumption) and another for inventory (stock).is a method for analyzing inventory based on, it posits that since revenue from items on inventory will be 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.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: machine, processing time variability, scraps, setups, time, lack of orders, lack of materials, 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 are: 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 define measures, that is an estimation of the maximum output of a given production system, and.(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 and variables. Choices in production technology involve: dimensioning, fractioning capacity, capacity location, processes, process technology, of operations, trade-off between volume and variety (see ). Choices in the organizational area involve: defining worker and, team coordination, worker incentives and information flow.Regarding, there is a basic distinction between the approach and the approach, with the later including the singular approach of. Pull means that the production system authorizes production based on inventory level; push means that production occurs based on demand (forecasted or present, that is ).

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. Classic EOQ model: trade-off between ordering cost (blue) and (red).

Total cost (green) admits a.Regarding the traditional pull approach to, a number of techniques have been developed based on the work of Ford W. Harris (1913), which came to be known as the (EOQ) model. This model marks the beginning of, which includes the, the, and the model. These models usually involve the calculation of and, the latter usually modeled as a function of demand variability. The economic production quantity (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. A typical MRPII construct: general planning (top) concerned with forecasts, capacity planning and inventory levels, programming (middle) concerned with calculation of, rough-cut capacity planning, MPS, traditional MRP planning, control (bottom) concerned with.and others at IBM developed a approach to inventory control and production planning, now known as (MRP), which takes as input both the (MPS) and the (BOM) and gives as output a schedule for the materials (components) needed in the production process. MRP therefore is a planning tool to manage 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 demand and 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.

And ). 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). When introducing kanbans in real production systems, attaining unitary lot from the start maybe unfeasible, therefore the kanban will represent a given lot size defined by management.A series of tools have been developed mainly with the objective of replicating Toyota success: a very common implementation involves small cards known as; these also come in some varieties: reorder kanbans, alarm kanbans, triangular kanbans, etc. A representation of materials and information flows inside a company, mainly used in the lean manufacturing approach. Main article: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. 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:. 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, 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.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.

Mathematical modeling. Illustration of the, a classical approach to solving optimization problems and also (ex: ). This technique is mainly used in push approach but also in production system configuration. The interior and surface of the green geometrically represent the, while the red line indicates the optimally chosen sequence of used to reach the.There are also fields of mathematical theory which have found applications in the field of operations management such as: mainly problems. Queue theory is employed in modelling queue and processing times in production systems while mathematical optimization draws heavily from. Queue theory is based on. Computations of are usually based on modeling demand as a and MRP and some inventory problems can be formulated using.When analytical models are not enough, managers may resort to using.

Simulation has been traditionally done through the 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 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. A control chart: output variable is modeled by a and for each of the an upper control line and lower control line are fixed.

Project Management Mba Program

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 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. The designation provides a summary of commonly used tools:. (Cause-and-effect diagram).These are used in approaches like. Keeping quality under control is relevant to both increasing customer satisfaction and reducing processing waste.Operations management usually cover, 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 dimensioning requires calculating the of. Demand forecasting is also a critical part of push systems, since order releases have to be planned ahead of actual clients’ orders.