Directing the Flow of Product: A Guide to Improving Supply by Jeffrey H Schutt

By Jeffrey H Schutt

As well as reviewing the state-of-the paintings in creation and distribution making plans, this advisor current rules and strategies during which organizations, together with digital businesses, can layout the right way to plan their operations.

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Extra info for Directing the Flow of Product: A Guide to Improving Supply Chain Planning

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Many authors (see, for example, Hopp and Spearman2) date the beginning of mathematical methods for managing operations to Ford W. Harris’s economic order quantity (EOQ) model of about 1913. Harris was one of the first to explicitly recognize the trade-off between the fixed cost associated with configuring machinery to make a specific part and the cost of holding inventory of that part, and then to turn that tradeoff into a mathematical model: a lot size formula. Our Heritage of Planning Techniques: The Tools in Our Toolbox 23 What is perhaps most noteworthy for our purposes is the realization we have come to over the last several decades that this model has very limited applicability in manufacturing.

Introduction to Product Flow Planning 13 between enterprises. We are now in a position to construct as much “brain” for both the enterprise and interenterprise supply chain as we believe will be acceptable to the participants, effective, and cost justified. With this freedom, the burden falls on the planning process designers to decide what kind of planning really needs to be performed, the degree of integration among plans, and how much development effort (or software license fee) we can justify.

By the early 1980s, the software was being extended to add distribution resource planning (DRP) capabilities (see Martin14). The DRP modules recognized that for products that must be stocked in many locations (for example, 28 Directing the Flow of Product food and many other consumer goods), the demand the master production schedule saw was not really independent (customer order or forecast) demand. The demand was actually dependent demand that could be netted up from current inventories in those multiple locations and expected depletion of those field inventories by forecasts or orders.

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