John C. Fisk

Production Lot Sizing Under A Learning Effect

Abstract Models are developed for determining optimal production lot sizes under a learning effect. These models consider situations in which both bounded and unbounded learning is assumed to occur. Bounded learning occurs when some nonzero lower limit is set on the time allowed to produce one unit of product.

Economic sizing of warehouses: A linear programming approach

Abstract Determining the best size for a private warehouse is a planning problem which can affect the overall operations of the firm for many years into the future. A linear programming formulation is presented which determines the optimal size warehouse to construct when demand is highly seasonal and public warehouse space is available on a monthly basis. The model is then extended for the dynamic sizing problem in which the warehouse size is allowed to change over time.

An interactive game for production and financial planning

Abstract This paper describes a computerized interactive game for use by students of business administration. The problem situation involves the need to determine an aggregate production plan for a small manufacturing firm which faces highly seasonal demand for its product. The student user is required to make decisions regarding planned manpower and production levels in future periods. In order to assist him in making these decisions, functional relationships describing pertinent production costs (wages, cost of hiring and firing, cost of carrying inventory) and financial costs (the cost of borrowing money to support production) are made available to the student decision maker.

Output planning for material requirements under uncertainty

This paper considers a production planning and control system requiring that, for each work station, a time-phased series of input and output values be estimated. It is assumed that the projected input levels can vary significantly across time periods and that anticipated output levels can be determined by management, subject to limits specified by available manpower and subcontracting. The actual input and output levels for each period depart from the planned levels according to a probability distribution determined empirically. An approach is presented that allows management to evaluate a chosen set of output levels to determine the probability that sufficient amounts of work will be available at a work station each period.

Application of work center control rules in a job shop environment

Abstract Work center control rules, defined as a combination of job dispatch rules and short-term work center capacity adjustments, are analyzed using queueing theory. Promising rules are evaluated with a job shop simulation model. Simulations comparing work center control rules to the critical ratio rule for job dispatching indicate that work center control can increase performance to customer due date while simultaneously reducing average work in process inventory. The work center control rules are easily implemented by shops currently using input/output control and daily dispatch lists.

Queue control using a historically developed stochastic model

Abstract This paper applies a stochastic model to determine the optimal or ideal average planned queue level. The ideal average planned queue level is defined to be the minimum average queue level necessary to ensure that in the long run the probability of work center idle time over a specified planning horizon is no greater than some value α chosen by management. Also discussed is the usefulness of the ideal planned queue level, not only for controlling work-in-process inventories, but also for obtaining better work center lead time estimates.