Suchergebnisse

ABSTRACTIn the past, performance in dynamic‐scheduling environments was primarily measured in terms of time or physical shop characteristics. Objectives such as mean tardiness, flow time, and work‐in‐process inventory were commonly used. Today, there is increasing interest in the use of more advanced economic performance measures. These measures have the more comprehensive objective of maximizing ownership wealth by economically scheduling jobs and tasks.This study presents a large‐scale experiment testing time‐based and economic‐based scheduling methods in a dynamic job shop. These methods are evaluated on their ability to maximize net present value (NPV). The study considers the just‐in‐time (JIT) delivery environment. The job shop is hypothetical, but is based on models of real production situations. Results show that the use of very detailed economic information in a sophisticated manner generally improves economic performance. Where due dates are easy to achieve, however, time‐based scheduling methods are at least as good as those based on economics. Also, where utilization is high and due dates tight, early cost information in release and dispatch is detrimental to schedule value.

AbstractA heuristic for 0–1 integer programming is proposed that features a specific rule for breaking ties that occur when attempting to determine a variable to set to 1 during a given iteration. It is tested on a large number of small‐ to moderate‐sized randomly generated generalized set‐packing models. Solutions are compared to those obtained using an existing well‐regarded heuristic and to solutions to the linear programming relaxations. Results indicate that the proposed heuristic outperforms the existing heuristic except for models in which the number of constraints is large relative to the number of variables. In this case, it performs on par with the existing heuristic. Results also indicate that use of a specific rule for tie breaking can be very effective, especially for low‐density models in which the number of variables is large relative to the number of constraints.

AbstractThis paper analyzes the problem of determining desirable spares inventory levels for repairable items with dependent repair times. The problem is important for repairable products such as aircraft engines which can have very large investment in spares inventory levels. While existing models can be used to determine optimal inventory spares levels when repair times are independent, the practical considerations of limited repair shop capacity and prioritized shop dispatching rules combine to make repair times not independent of one another. In this research a simulation model of a limited capacity repair facility with prioritized scheduling is used to explore a variety of heuristic approaches to the spares stocking decision. The heuristics are also compared with use of a model requiring independent repair times (even though that assumption is not valid here). The results show that even when repair time dependencies are present, the performance of a model which assumes independent repair times is quite good.

ABSTRACTWhile the majority of the literature on shop scheduling has emphasized time‐based performance criteria such as mean flow time, lateness, and tardiness, the primary goal of management should be the maximization of shop profitability. In this research the net present value (NPV) criterion is introduced to measure shop profitability. This measure combines aspects of job flow time and inventory holding costs into a single measure. A simulation model of a job shop is used to examine the performance of a variety of time‐ and value‐based scheduling rules. These rules are evaluated with respect to the NPV criterion in both random and flow shop environments. The results suggest that priority rules that utilize monetary information about jobs yield a higher NPV than many time‐based rules in most situations, with little sacrifice in job tardiness. A well‐researched time‐based rule, critical ratio, also provides excellent performance when the shop is heavily loaded.

The cost of materials has often been neglected by managers faced with the problem of reducing manufacturing costs. However, as direct labour, the classical cost reduction target, is reduced by automation the task of reducing materials cost has become much more urgent. As a result of this pressure new approaches have been developed to address the reduction of materials costs. This article reviews and describes five such approaches.

White‐collar productivity measurement can be improved, according to results from group sessions conducted with 39 executives, managers and academics which elicited a list of eleven useful areas for measurement. There are three types of ways in which the measurements can be used: self‐improvement; performance appraisal, salary and promotion; and feedback, communication and work direction. Highly interactive jobs should be measured at group level, with individual performance judged on the basis of group results. Peer group ratings can also measure white collar productivity, with existing MBO systems providing information; and time management techniques are also appropriate.