Operations Management is an area of business that is concerned with the production of goods and services, and involves the responsibility of ensuring that business operations are efficient and effective. It is also the management of resources, the distribution of goods and services to customers, and the analysis of queue systems.
Supply Chain Management (SCM) is the process of planning, implementing, and controlling the operations of the supply chain with the purpose to satisfy customer requirements as efficiently as possible. Supply chain management spans all movement and storage of raw materials, work-in-process inventory, and finished goods from point-of-origin to point-of-consumption. The term supply chain management was coined by consultant Keith Oliver, of strategy consulting firm Booz Allen Hamilton in 1982.
The definition one America professional association put forward is that Supply Chain Management encompasses the planning and management of all activities involved in sourcing, procurement, conversion, and logistics management activities. Importantly, it also includes coordination and collaboration with channel partners, which can be suppliers, intermediaries, third-party service providers, and customers. In essence, Supply Chain Management integrates supply and demand management within and across companies. Supply chain event management (abbreviated as SCEM) is a consideration of all possible occurring events and factors that can cause a disruption in a supply chain. With SCEM possible scenarios can be created and solutions can be planned. Some experts distinguish supply chain management and logistics, while others consider the terms to be interchangeable. Supply chain management is also a category of software products.
This course is a survey of the major concepts and techniques used to manage the operations function. The course considers both managerial and analytical issues, since an effective manager must be proficient in both areas. Specifically, we will 1. Develop a basic understanding of the manufacturing/operations function and its importance for the smooth operation of the firm. 2. Build an understanding of the integration of the manufacturing and operations function into the corporate strategy. 3. Introduce a representative subset of the basic problem-solving and data analysis techniques to assist the operations manager in making "good" decisions. The further objectives of this course are: to understand the strategic role of supply chains; to learn about the opportunities and problems faced by supply chain managers in manufacturing and service organizations; to become familiar with common supply chain management principles and decision-making techniques; and to develop the ability to apply these techniques in a variety of settings. The instructor's role will be to emphasize key insights from the reading and graded homework assignments, elaborate on major concepts and themes, demonstrate analytical techniques, and provide timely feedback about student performance.
Teaching and Learning Resources Click on titles for further details
Introduction to Operations Management.
The Operating Leverage is a measure of how revenue growth translates into growth in operating income. It can be a ratio of fixed costs to variable costs incurred to generate the revenue. Depending on the product, it can be generated by the ratio of preproduction costs (i.e. design widgets) versus incremental production costs (i.e. produce a widget). The two, fixed costs and variable costs are the operating expenses. The ratio between the two determines how growth in revenue impacts the operating margin. If the variable costs are all the operating costs, then the operating margin would be constant as sales grow. A 10% increase in revenue generates a 10% increase in operating income. If, however, fixed costs are high, then a 10% increase in revenue will generate quite a bit more than 10% increase in operating earnings, essentially increasing the operating margin. See also External links
Processes in Manufacturing and Services. Financial Analysis in Operations Management. Process Measurement and Analysis. Tutorials
Readings Manufacturing Process Management (MPM) is a collection of technology and methods used in the manufacture of products. It incorporates such technologies as computer-aided production engineering (CAPE), Advanced Planning & Scheduling (APS) , computer-aided manufacturing (CAM), Manufacturing Execution System (MES) , computer-aided quality assurance (CAQ), the utilization of CAD and AEC tools for factory layout and digital mockup (DMU) and simulation for assembly analysis. As the digital manufacturing part of the PLM process it is the bridge from product design to production planning and on to resource and inventory scheduling. As CAD defines what is to be made; and ERP/MRP defines when it is to be made; MPM defines how it will be made. A cornerstone of MPM is the central repository for manufacturing data management (MDM) similar to PDM for design data. MPM takes the product data eBOM (engineering Bill of Material) to create the process oriented mBOM (manufacturing) along with a bill of process (BOP). This together with the management of resources such as tools, machines and work centers forms the so called 3PR data (product process plant resources). The integration of all these tools and activities aids in the exploration of alternative production line scenarios; making assembly lines more efficient with the aim of reduced lead time to product launch, shorter product times and reduced work in progress (WIP) inventories as well as allowing rapid response to product or product changes.
Business Process Reengineering is a management approach aiming at improvements by means of elevating efficiency and effectiveness of the processes that exist within and across organizations.
Business process reengineering is also known as BPR, Business Process Redesign, Business Transformation, or Business Process Change Management.
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Quality Management. Statistical Quality Control Methods. Tutorials Readings Quality Management is a method for ensuring that all the activities necessary to design, develop and implement a product or service are effective and efficient with respect to the system and its performance.
Six Sigma is a system of practices originally developed by Motorola to systematically improve processes by eliminating defects.[1] Defects are defined as units that are not members of the intended population. Since it was originally developed, Six Sigma has become an element of many Total Quality Management (TQM) initiatives.
The process was pioneered by Bill Smith at Motorola in 1986[2] and was originally defined[3] as a metric for measuring defects and improving quality, and a methodology to reduce defect levels below 3.4 Defects Per (one) Million Opportunities (DPMO). Six Sigma is a registered service mark and trademark of Motorola, Inc.[4] Motorola has reported over US$17 billion in savings[5] from Six Sigma as of 2006. In addition to Motorola, companies which also adopted Six Sigma methodologies early-on and continue to practice it today include Bank of America, Caterpillar, Honeywell International (previously known as Allied Signal), Raytheon and General Electric (introduced by Jack Welch). Recently Six Sigma has been integrated with the TRIZ methodology for problem solving and product design.
Forecasting Tutorials Readings Forecasting is the process of estimation in unknown situations. Prediction is a similar, but more general term, and usually refers to estimation of time series, cross-sectional or longitudinal data. In more recent years, Forecasting has evolved into the practice of Demand Planning in every day business forecasting for manufacturing companies. The discipline of demand planning, also sometimes referred to as supply chain forecasting, embraces both statistical forecasting and consensus process. Forecasting is commonly used in discussion of time-series data.
Waiting Line Management. Waiting Line Theory. Tutorials Readings Queueing Theory (also commonly spelled queuing theory) is the mathematical study of waiting lines (or queues). The theory enables mathematical analysis of several related processes, including arriving at the (back of the) queue, waiting in the queue (essentially a storage process), and being served by the server(s) at the front of the queue. The theory permits the derivation and calculation of several performance measures including the average waiting time in the queue or the system, the expected number waiting or receiving service and the probability of encountering the system in certain states, such as empty, full, having an available server or having to wait a certain time to be served. Queueing theory is generally considered a branch of operations research because the results are often used when making business decisions about the resources needed to provide service. It is applicable in a wide variety of situations that may be encountered in business, commerce, industry, public service and engineering. Applications are frequently encountered in customer service situations as well as transport and telecommunication and it is occasionally linked to ride theory. Queueing theory is directly applicable to intelligent transportation systems, call centers, PABXs, networks, telecommunications, server queueing, mainframe computer queueing of telecommunications terminals, advanced telecommunications systems, and traffic flow.
Human Resource Issues in OM. Work Performance Measurement. Tutorials Readings Performance Management may mean: Performance measurement is the process of assessing progress toward achieving predetermined goals, while performance management is building on that process adding the relevant communication and action on the progress achieved against these predetermined goals (Bourne, M.,Franco, M. and Wilkes, J. (2003). Corporate performance management. Measuring Business Excellence; 2003; 7, 3; p. 15)
Simply put, performance management helps organizations achieve their strategic goals. Rather than discarding the data accessibility previous systems fostered, performance management harnesses it to help ensure that an organization’s data works in service to organizational goals to provide information that is actually useful in achieving them. and focus on the Operational Networking Processes between that performance level. External links
Workshop
Project Management. Aggregate Planning. Operations Strategy. Tutorials
Readings Project Management is the discipline of organizing and managing resources in such a way that these resources deliver all the work required to complete a project within defined scope, quality, time and cost constraints. A project is a temporary and one-time endeavor undertaken to create a unique product or service, that brings about beneficial change or added value. This property of being a temporary and a one-time undertaking contrasts with processes, or operations, which are permanent or semi-permanent ongoing functional work to create the same product or service over and over again. The management of these two systems is often very different and requires varying technical skills and philosophy, hence requiring the development of project management. The first challenge of project management is to ensure that a project is delivered within defined constraints. The second, more ambitious challenge is the optimized allocation and integration of inputs needed to meet pre-defined objectives. A project is a carefully defined set of activities that use resources (money, people, materials, energy, space, provisions, communication, quality, risk, etc.) to meet the pre-defined objectives. |
