Key Terms

  • Buffer

    A means or device used as a cushion against the shock of fluctuations in business or financial activity. Due to variability, the demand flow and the process flow never perfectly synchronize, and some sort of buffer is required when matching process output to demand.

    The only buffers available are:

    • Inventory—transformation occurs before demand
    • Time—transformation occurs after demand
    • Capacity—above the average demand.
    See Also: Inventory
  • Capacity

    The maximum average rate at which the items/units/tasks/products can flow through a process or system. Capacity is the upper limit of throughput. Having installed capacity above average demand allows the Stock Inventory and Backorder Time buffers to remain small.

    If the process had infinite capacity, there would never be either Stock or Backorders as the process could satisfy demand instantly.”

    See Also: Process
  • Constraint

    In Project Production Control, a constraint is a predecessor task that must be completed in order for work to flow through the process. This is different usage than occurs often in traditional production where the term constraint is also used to mean bottleneck.

    See Also: Bottleneck
  • Flow

    A flow is a collection of production or service routings or a collection of demand streams. A flow represents materials or resources moving through the transformation process, A flow is described by a rate. The measure of a flow is some unit or task per period of time, e.g. barrels per day or service calls
    per day.

    A flow can be a set of operations called a process that accomplishes transformation. A flow can also be a set of individuals creating the demand for the transformed entities. The rate of flow for a process is called its throughput.

  • Inventory

    The accumulation of entities that occurs anywhere within and/or between processes (flows).

    Inventory between two or more flows is called stock while inventory within a flow is called work in process or WIP.

    One of the primary underlying tenets of Project Production Management (PPM) is that operators can and should be calculating the appropriate level of inventory required within and between each task in their project.

  • Kingman’s Equation (VUT equation)

    In queueing theory, a discipline within the mathematical theory of probability, Kingman’s formula is an approximation for the mean waiting time in a queue in a system with a single server where arrival times have a general (meaning arbitrary) distribution and service times have a (different) general distribution. It is generally represented as CT = VUT, where CT is Cycle Time, V is a factor representing variability, U is a factor representing utilization, and T represents the mean effective process time.

  • Line of Balance

    The “Line of Balance” (LOB) is a graphic device that enables a manager to see at a single glance which of many activities comprising a complex operation are “in balance” ­ i.e., whether those which should have been completed at the time of the review actually are completed and whether any activities scheduled for future completion are lagging behind schedule. History: LOB was devised by the members of a group headed by George E. Fouch. During 1941, the Goodyear Tire & Rubber Company monitored production with LOB. It was successfully applied to the production planning and scheduling of the huge Navy mobilization program of World War ll. LOB proved to be a valuable tool for expediting production visibility during the Korean hostilities. During this period, defense suppliers used LOB http://www.valuation-opinions.com/ev/lob.lasso.

    Source: Line of Balance Technology: A graphic method of industrial programming, US Department of Navy, April 1962

  • Little’s Law

    The relationship between system throughput (TH), cycle time (CT), and work­ in­ process (WIP).

    Cycle time is a dependent variable. WIP is a leading indicator of CT.

    Sources: Factory Physics, Third Edition, Wallace J. Hopp and Mark L. Spearman, Waveland Press, p 239, Queues, Inventories and Maintenance: The Analysis of Operational Systems with Variable Demand and Supply, P. M. Morse, Dover, 2004, p 22, A Proof for the Queuing Formula: L = lW, J. D. C. Little, Operations Research, Volume 9, Issue 3, pp 383-387, Little’s Law as viewed on its 50th Anniversary, J. D. C. Little, Operations Research, Volume 59, Issue 3, pp 536-549
  • Operations Management

    Operations Management is the application of operations science to real­-world production, service, and distribution systems. This includes supply chain management as well. Operations management is concerned with the design, control and improvement of any organization’s operations.

  • Operations Research (OR)

    The application of mathematical (quantitative) techniques to the scientific study and analysis of complex systems and optimization problems of organization and coordination of activities in business operations and decision making.

    Historically the discipline emerged as the confluence of several different threads of scientific application. Charles Babbage conducted research into the cost of transportation and sorting of mail which were applied in the UK’s first postal system. To understand the best choice of railway gauge, he conducted studies into dynamical behavior of railway vehicles on a railway network. Military planners during World War 1 were concerned with the scientific planning and organization of logistics of supplies for troops (convoy theory and Lanchester’s laws). The field expanded with the Second World War conferring several problems for US and UK military planners resulting in the development (among other things) of linear and dynamic programming techniques, and other mathematical tools.

    Since then, the field has found application in many areas in transportation, finance, logistics
    and government.

    Operations Research tends to be heavily focused on complex mathematical models to solve a specific problem as mentioned above. Operations Science provides first principle observations about the behavior of nature. Operations Research techniques can be used to test any of these observations.

  • Operations Science

    The study of the transformation of resources to create and distribute goods and services.

    Operations Science (OS) focuses on the interaction between demand and production and the variability associated with either or both. OS also describes the set of buffers required to synchronize demand with production.

  • Process

    A set of one or more operations designed to transform a set of entities into another form to achieve a particular purpose. A process may result in production of a physical product or completion of a service. A project is a collection of service and production processes.

    Examples of processes include production lines, construction projects, hospital operating theaters, insurance claims processing and Discrete Event Simulation analysis. Also called a Value Stream.

  • Production Control

    Policies, protocols and mechanisms to control transformational processes and the accompanying use of resources and variability levels.

  • Production System

    A specific or defined set of operations within a larger supply network or value chain that produces technical or physical output to satisfy an external demand.

  • Project Production Management

    The development and application of modern production theories, principles and methods to better understand, control and improve project delivery. This includes the application of Operations Science, digital and autonomous technologies.

  • Station Cycle Time Formula

    The Station Cycle time formula states that the average cycle time at a station in a production system includes actual Processing Time (PT), as well as Move Time (MT), Setup Time (ST), Queuing Time (QT), Batch Time (BT) (CT=PT + MT + QT + ST + BT) Cycle time for an end-to-end process is CT = PT + MT + SDT + BT + QT where SDT represents the shift differential time.

  • Variability

    The term used to describe any dissimilarity between specific instances of a particular operation or process, particular entity output from an operation, or a particular demand. The dissimilarity may manifest itself in terms of attributes of the entities/ operations or in the timing of those entities/operations.

  • Work in Process (WIP)

    Work in process or WIP is the set of entities that are partially transformed within any given process. WIP does not include stock inventory which is composed of completed entities.

    WIP typically accumulates while waiting for available capacity in front of an operation. Stock accumulates between two or more processes (e.g., finished inventory between a process and its demand).

    Chart showing the relationships among Throughput, Cycle Time and WIP

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