page_title: Operations management
section_title: Configuration and management
hierarchical_section_title: Operations management / Topics / Configuration and management
caption_attribution_description: Current State Value Stream Map with Environmental Data
context_page_description: Operations management is an area of management concerned with designing and controlling the process of production and redesigning business operations in the production of goods or services. It involves the responsibility of ensuring that business operations are efficient in terms of using as few resources as needed and effective 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 or service system which is the process that converts inputs into outputs. Operations produce products, manage quality and create services. Operation 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.
context_section_description: Designing the configuration of production systems involves both technological and organizational variables. Choices in production technology involve: dimensioning capacity, fractioning capacity, capacity location, outsourcing processes, process technology, automation of operations, trade-off between volume and variety (see Hayes-Wheelwright matrix). Choices in the organizational area involve: defining worker skills and responsibilities, team coordination, worker incentives and information flow.
  Regarding production planning, there is a basic distinction between the push approach and the pull approach, with the later including the singular approach of just 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 is purchase 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.
  Regarding the traditional pull approach to inventory control, a number of techniques have been developed based on the work of Ford W. Harris (1913), which came to be known as the economic order quantity (EOQ) model. This model marks the beginning of inventory theory, which includes the Wagner-Within procedure, the newsvendor model, base stock model and the Fixed Time Period model. These models usually involve the calculation of cycle stocks and buffer stocks, 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.
  Joseph Orlickly and others at IBM developed a push approach to inventory control and production planning, now known as material requirements planning (MRP), which takes as input both the master production schedule (MPS) and the bill 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 manage 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 capacity and fixed lead times, which influenced successive modifications of the original software architecture in the form of 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.
  Lean manufacturing is an approach to production which arose in Toyota between the end of World War II and the seventies. It comes mainly from the ideas of Taiichi Ohno and Toyoda Sakichi which are centered on the complementary notions of just in time and autonomation (jidoka), all aimed at reducing waste (usually applied in PDCA style). Some additional elements are also fundamental: production smoothing (Heijunka), capacity buffers, setup reduction, cross-training and plant layout.
  Heijunka: production smoothing presupposes a level strategy for the MPS and a final assembly schedule developed from the MPS by smoothing aggregate production requ
caption: 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.