Customer Order Scheduling in a General Job Shop Environment*

The primary objective of this study is to examine the performance of order-based dispatching rules in a general job shop, where the environmental factors are shop utilization and due date tightness. An order is defined as a collection of jobs that are shipped as a group—an order—to the customer, only on completion of the last job of the order. We specifically compare dispatching rules from past job-based studies to some rules adapted to encompass order characteristics. Standard flow time and tardiness measures are used, but in addition, we introduce measures that combine average performance with variation in an attempt to capture the performance of a majority of the orders processed in the shop. Of the 16 dispatching rules tested, our results show that four of the simple rules dominate the others. We also found that order-based rules perform better than their job-based counterparts. The study makes use of multivariate statistical analysis, in addition to the usual univariate tests, which can provide additional insight to managers using multiple criteria in their decision process.     

Lot Splitting in Stochastic Flow Shop and Job Shop Environments*

In recent years many firms have been implementing small lot size production. Lot splitting breaks large orders into smaller transfer lots and offers the ability to move parts more quickly through the production process. This paper extends the deterministic studies by investigating various lot splitting policies in both stochastic job shop and stochastic flow shop settings using performance measures of mean flow time and the standard deviation of flow time. Using a computer simulation experiment, we found that in stochastic dynamic job shops, the number of lot splits is more important than the exact form of splitting. However, when optimal job sizes are determined for each scenario, we found a few circumstances where the implementation of a small initial split, called a “flag,” can provide measurable improvement in flow time performance. Interestingly, the vast majority of previous research indicates that methods other than equal lot splitting typically improves makespan performance. The earlier research, however, has been set in the static, deterministic flow shop environment. Thus, our results are of practical interest since they show that the specific method of lot splitting is important in only a small set of realistic environments while the choice of an appropriate number of splits is typically more important.     

RFID as an Enabler of Improved Manufacturing Performance*

The use of radio frequency identification (RFID) versus bar coding has been debated with little quantitative research about how to best use RFID's capabilities and when RFID is more advantageous. This article responds to that need by qualitatively and quantitatively analyzing how RFID facilitates increased traceability and control in manufacturing, which in turn enables the use of more lot splitting and smaller lot sizes. We develop insights about operating policies (RFID vs. bar‐code tracking mechanisms, extent of lot splitting, and dispatching rules) and an operating condition (setup to processing time ratio) that affect the mean flow time and proportion of jobs tardy in a job shop. A simulation model is used to control factors in the experimental design and the output is evaluated using analysis of variance. The results show the following: (i) performance worsens when bar coding is used with extensive lot splitting, (ii) process changes such as extensive lot splitting may be required to justify RFID use instead of bar coding, (iii) the earliest operation due date dispatching rule offers an attractive alternative to other rules studied in previous lot splitting research, and (iv) the performance improvements with RFID and increased lot splitting are larger when the setup to processing time ratio is smaller. In a broader context, we fill a research void by quantitatively showing how RFID can be used as an advanced manufacturing technology that enables more factory automation and better performance along several dimensions. The article concludes by summarizing the results and identifying ideas for future research.     

Replanning the Master Production Schedule for a Capacity-Constrained Job Shop

This research examines the use of both frozen and replanning intervals for planning the master production schedule (MPS) for a capacity-constrained job shop. The results show that forecast error, demand lumpiness, setup time, planned lead time, and order size have a greater impact on the mean total backlog, total inventory, and number of setups than the frozen and replanning intervals. The study also shows that a repetitive lot dispatching rule reduces the importance of lot sizing, and a combination of repetitive lot dispatching rule and single-period order size consistently produces the lowest mean total backlog and total inventory. The results also indicate that rescheduling the open orders every period produces a lower mean total backlog and total inventory when the forecast errors are large relative to the order sizes. This result suggests that the due date of an open order should be updated only when a significant portion of the order is actually needed on the new due date.     

A Virtual Cellular Manufacturing Approach to Batch Production*

In this paper, Virtual Cellular Manufacturing (VCM), an alternative approach to implementing cellular manufacturing, is investigated. VCM combines the setup efficiency typically obtained by Group Technology (GT) cellular manufacturing (CM) systems with the routing flexibility of a job shop. Unlike traditional CM systems in which the shop is physically designed as a series of cells, family-based scheduling criteria are used to form logical cells within a shop using a process layout. The result is the formation of temporary, virtual cells as opposed to the more traditional, permanent, physical cells present in GT systems. Virtual cells allow the shop to be more responsive to changes in demand and workload patterns. Production using VCM is compared to production using traditional cellular and job shop approaches. Results indicate that VCM yields significantly better flow time and due date performance over a wide range of common operating conditions, as well as being more robust to demand variability.     

The Value of Using Scheduling Information in Planning Material Requirements*

Current research and practice in the field of production and inventory planning is dominated by hierarchical, material requirements planning-based methods. The objective of this research is to determine the merits of a major redirection for the design of manufacturing planning systems—a direction that more directly exploits the capabilities of modern computer technology. We test the relative performance of two fundamentally different classes of manufacturing planning systems: (1) those that make no use of sequencing and scheduling information in the planning of material deliveries (for example, traditional MRP-based systems), and (2) those that use sequencing and scheduling information to plan delivery of materials. We first derive an analytical expression for the expected benefit (in terms of flow time reduction) of using scheduling information for a single machine system. We then describe and test a simple heuristic for predicting the improvement that could be realized in more complicated multimachine systems, under certain conditions. Results from controlled simulation experiments, over a wide range of operating environments, suggest that although the value of scheduling information is influenced by the operating environment, it could be substantial.     

Due Date Assignment,Job Order Release,and Sequencing Interaction in Job Shop Scheduling*

Depending on the techniques employed, the due date assignment, release, and sequencing procedures in job shop scheduling may depend on one another. This research investigates the effects of these interactions with a simulation model of a dynamic five-machine job shop in which early shipments are prohibited. Performance of the system is measured primarily in terms of the total cost (work-in-process cost, finished goods holding cost, and late penalty) incurred by the shop, but a number of non-cost performance measures are also reported. The results support existence of a three-way interaction between the due date, release, and sequencing procedures as well as interaction between shop utilization and procedure combination. Statistical tests are used to identify those rules that perform best both overall and in combination with other rules.     

An Investigation of Scheduling Policies in a Dual-Constrained Manufacturing Cell*

In previous group scheduling studies, labor has essentially been ignored by assuming that enough labor is assigned to each machine in the cell. In reality, however, management usually does not have the resources to employ a laborer at each machine in the cell (i.e., machines need to share labor). Both labor scheduling and group scheduling heuristics need to be administered to manage the cell effectively. This study develops and examines scheduling procedures for a dual-constrained (i.e., machine and labor) manufacturing cell. Eleven decision rules are developed and tested under 16 different experimental conditions. The experimental factors used are interarrival time distribution, cell load, setup-to-run-time ratio, and transfer-to-run-time ratio. Results show that interarrival time distribution and cell load have the greatest impact on the performance of the cell. This suggests that effective production planning aimed at reducing job arrival variation and leveling the cell load can substantially improve cell performance. Among the experimental factors, setup and transfer-to-run-time ratio factors had the strongest influence on the rankings of the decision rules. These rankings were fairly robust across all experimental conditions and performance measures. The results also indicated that the inclusion of labor as a contraint in the cell had a significant impact on the performance of several group scheduling heuristics. Finally, it was shown that the best performing decision rules consider both transfer time and subfamily setup times.     

An Evaluation of Capacity Sensitive Order Review and Release Procedures in Job Shops

We investigate the performance of capacity-sensitive order review and release (ORR) procedures in job shop environments that have not been previously explored. Previous research has ignored the case of job shops which must perform to very tight due-dates because of time-sensitive customers. We propose and test a new capacity sensitive ORR procedure called path based bottleneck (PBB) in such environments, along with the modified infinite loading (MIL) procedure which has been shown to work well in several studies. We compare the performance of these two controlled release rules with that of immediate release rule under different conditions of capacity utilization and customer specified exogenous duedates. Our results indicate that PBB performs well in lowering total costs when due-dates are tight, while MIL is a better procedure with relatively loose to medium due-dates. We also show that in many cases, the shortest processing time (SPT) dispatching rule is a superior performer than a due-date based rule like critical ratio (CR); a conclusion which is contrary to the existing research in this area. In addition, the shop floor control policies recommended are shown to be sensitive to the cost structure of the firm. The managerial implications of this research in providing effective shop floor control in job shops operating under tight due-date conditions are also discussed.     

Open Order Rescheduling in Job Shops with Demand Uncertainty: A Simulation Study

This paper addresses the problem of open order rescheduling in a job shop. Results are reported of experiments conducted in a simulation model of an 8-machine job shop. Four different order updating policies are examined. The due-date process is modeled to include several realistic features about the pattern of due-date variability. These features are parameterized and tested at several levels. Tardiness results indicate that open order rescheduling is beneficial only when allowances are loosely set. The results indicate that inventory performance is improved by order rescheduling, particularly in cases when due dates are revised to earlier times than originally forecast.     

Alternate Routing Strategies in Batch Manufacturing: An Evaluation

Batch manufacturing firms are experiencing significant changes because of technological developments in work center design, such as flexible manufacturing systems (FMS) and planning/control tools like computer-aided process planning (CAPP). These new developments provide production managers with some solutions to a number of complex problems. For example, numerical-controlled (NC) machine center installations are effective in providing quality parts because of tight tolerance specifications built into the equipment. However, these highly efficient centers create bottlenecks that constrain shop throughput, since production planners tend to rely too much on them. To help improve manufacturing planning, we introduce an important element to the batch production scheduling component of CAPP's mission—evaluating possible alternate routes. Production scheduling encompasses job route selection as well as machine center assignment (loading), job releasing, and setting due dates. In this paper, three routing strategies requiring different levels of shop floor information are tested and evaluated using computer simulation. Shop performance is measured by total cost and traditional measures of job flow time, lateness, and tardiness.     

Integrative Cycle Scheduling Approach for a Capacitated Flexible Assembly System*

This study revisits the traditional single stage, multi-item, capacitated lot-sizing problem (CLSP) with a new integrative focus on problem structuring. Unlike past research, we develop integrative cycle scheduling approaches which simultaneously address lot-sizing, capacity, and sequencing issues. Our purposes are to (1) explore the effect of sequencing on inventory levels, (2) examine the problem of infeasibility in the economic lot scheduling problem (ELSP), and (3) provide a simple methodology of generating low-cost cycle schedules in an environment with discrete shipping, dynamic demands, limited capacity, zero setup cost, and sequence-independent setup times. Our procedures are compared to benchmark cycle scheduling approaches in terms of both inventory cost and computation time under different demand scenarios, using the operating data from a flexible assembly system (FAS) at the Ford Motor Company's Sandusky, Ohio plant.     

Management Policies to Improve the Effectiveness of Multi-Station Service Organizations*

A SLAM based simulation model of a multi-station, tandem queuing structure characteristic of a variety of service systems is employed to test various design options for the system. The model is based on an extensive study of the State of Florida driver licensing offices. The multiple objectives of low time in the system for customers and the efficient use of personnel resources are employed to measure the benefits of policy options. The use of simulation analysis permits the incorporation of complex system characteristics, therefore providing a realistic representation of the effects of possible management actions. Effective methods to control labor in such systems are suggested.     

Cross‐training Decisions in Field Services with Three Job Types and Server–Job Mismatch*

To be cost‐effective, field service managers must balance the high cost of machine downtime with the high cost of cross‐training technicians in multiple skills. We study a field service system with three job types requiring three different skills. Each server has a primary skill, the cost of which is considered sunk, and up to two secondary skills, which is a managerial decision. We model two important characteristics that distinguish field services: server–job mismatch and the ratio of travel time to service time. We use a queueing framework and simulation to study three cross‐training decisions: the number of servers cross‐trained in secondary skills, the number of secondary skills each server should have, and the efficiency in each secondary skill. We find that complete cross‐training is cost‐effective in some field service situations. Typically, efficiency in secondary skills must be close to 100%, but when the probability of mismatch is high and the ratio of travel time to service time is high, efficiency in secondary skills must be less than 100%.     

Shop Floor Control When Tacit Worker Knowledge is Important

We investigate a shop where the workers and supervisors have tacit knowledge of how to operate efficiently and where efficiency is important to providing capacity to meet demand. This tacit knowledge includes setup dependencies between products as well as which worker or machine is best suited for a particular product. We discuss a real‐world shop where this is the case. Management expects workers and supervisors to use their knowledge to schedule efficiently by monitoring their performance based on standards. The question that we explore is how management should control for due date performance in light of the discretion given to the workers and supervisors to sequence jobs on the basis of efficiency. We explore management control of due date performance through the use of order review and release (ORR) and management expediting. We find that although ORR is quite effective at reducing work‐in‐process (WIP) inventories, it may foster very late deliveries in a shop such as this. In fact, under such conditions, deftly executed expediting with no ORR at all can be far more effective at supporting all deliveries. Even improving ORR into a hybrid by actively updating path efficiencies (observed from supervisor/worker scheduling) did not support a change to this conclusion. Conversely, when conditions are created where tacit knowledge plays a reduced role or utilization is decreased, ORR delivers in a timely manner. The interaction between utilization, WIP levels, and worker knowledge all help dictate the appropriate control methodology.     

An Experimental Comparison of Dispatching Rules for Field Service Support*

Field service repair management is increasing in importance as “high tech” machines such as computers, communication systems, and copy machines are becoming more popular and more widely disbursed geographically. Complicating the management of these systems are response time performance guarantees (e.g., 8-hour response time), which are a popular marketing tool for many field service businesses [21]. These response time), guarantees especially complicate the field service dispatching problem. With response time guarantees, dispatchers must consider travel times and other issues to determine which call should be assigned to an available technician. This research proposes several dispatching rules that might be applied for dispatching sequential-trip technicians in this environment and compares these rules in a simulation experiment to determine which rule is best in terms of average tardiness. The proposed composite travel time-expiration time rule was found to be the best on average tardiness performance and on all other tardiness-related measures. Given the increased importance of tardiness performance in field service organizations, the proposed composite rule appears to have promise.     

An Experimental Comparison of Time-Based and Economic-Based Scheduling Methods to Maximize Net Present Value*

In 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.     

The Critical Few Minutes in Scheduling Time‐Varying Queuing Systems

For nonstationary queuing systems where demand varies over time, an important practical issue is scheduling the number of servers to be available at various times of the day. Widely used scheduling procedures typically involve adding servers at natural time points (e.g., on the hour or at half past the hour) during peak demand periods. Scheduling is often complicated by restrictions on the minimum amount of time (human) servers must work, the earliest (or latest) time a server is available, and limits on the maximum number of servers that can be used at any one time. This paper was motivated by experience with actual queuing systems that embodied such complications. For these systems common scheduling methods that used “natural” starting times for servers resulted in needlessly long customer waits. This research demonstrates that changing the starting times of servers by only a few minutes can have dramatic impacts on customer waiting times for extended periods. In addition, the results highlight the importance of server punctuality.     

An investigation of order release and flow time allowance policies for assembly job shops

The effects of a number of essentially different work order release and flow time allowance policies on the assembly order flow times and assembly order due date performance are investigated. Work orders within an assembly order have different routing length. The assembly order flow time is the time that elapses between the release of the first work order and the completion of the last work order of the assembly order. The timing of the release of work orders, and the distribution of the flow time allowance over the work orders in an assembly order were varied, and used systematic computer simulation to investigate the effects on performance. The results show that the best performance is obtained with simultaneous work order release, an average operation flow time allowance equal to the average operation waiting time and equalized flow time allowances per work order in an assembly order.     

Evaluation of scheduling strategies for a dynamic job shop in a tool-shared,flexible manufacturing environment

A two-phase approach is used to examine the impact of job scheduling rules and tool selection policies for a dynamic job shop system in a tool-shared, flexible manufacturing environment. The first phase develops a generalized simulation model and analyses 'simple' job scheduling rules and tool selection policies under various operating scenarios. The results from this investigation are then used to develop and analyse various bi-criteria rules in the second phase of this study. The results show that the scheduling rules have the most significant impact on system performance, particularly at high shop load levels. Tool selection policies affect some of the performance measures, most notably, proportion of tardy jobs, to a lesser degree. Higher machine utilizations can be obtained at higher tool duplication levels but at the expense of increased tooling costs and lower tool utilization. The results also show that using different processing time distributions may have a significant impact on shop performance.