Workload control and optimised order release: an assessment by simulation

An important scheduling function of manufacturing systems is controlled order release. While there exists a broad literature on order release, reported release procedures typically use simple sequencing rules and greedy heuristics to determine which jobs to select for release. While this is appealing due to its simplicity, its adequateness has recently been questioned. In response, this study uses an integer linear programming model to select orders for release to the shop floor. Using simulation, we show that optimisation has the potential to improve performance compared to ‘classical’ release based on pool sequencing rules. However, in order to also outperform more powerful pool sequencing rules, load balancing and timing must be considered at release. Existing optimisation-based release methods emphasise load balancing in periods when jobs are on time. In line with recent advances in Workload Control theory, we show that a better percentage tardy performance can be achieved by only emphasising load balancing when many jobs are urgent. However, counterintuitively, emphasising urgency in underload periods leads to higher mean tardiness. Compared to previous literature we further highlight that continuous optimisation-based release outperforms periodic optimisation-based release. This has important implications on how optimised-based release should be designed.     

Job sequencing and selection within workload control order release: an assessment by simulation

Recent research has highlighted the potential impact of pool sequencing on order release performance but it suffered from two shortcomings. First, arguably the best release solution for workload control in practice combines periodic with continuous release. Although the two types of releases serve different functions, recent work assumed the same sequencing rule should be used for both. Here, the use of different sequencing rules for periodic and continuous releases is evaluated. Using a job-shop simulation, we demonstrate that the rule applied during continuous releases has only a negligible impact on performance. Therefore, jobs can be pulled intermediately from the pool by workers using a more straightforward sequencing rule than the one applied for periodic release. Second, it was assumed that all jobs in the pool are sequenced and then a subset is selected for release. But for some load-oriented sequencing rules, the priority value used for sequencing jobs should be updated after each job selection from the pool. Our simulation results show that although this may improve load balancing at release, it does not in fact improve overall shop performance. Therefore, the greedy heuristic of first sequencing and then selecting jobs can be maintained, which allows the release decision-making process to retain its simplicity. The work has important implications for the use of sequencing rules in practice.     

On the beat of the drum: improving the flow shop performance of the Drum–Buffer–Rope scheduling mechanism

One of the main elements of the theory of constraints is its Drum–Buffer–Rope (DBR) scheduling (or release) mechanism that controls the release of jobs to the system. Jobs are not released directly to the shop floor – they are withheld in a backlog and released in accordance with the output rate of the bottleneck (i.e. the drum). The sequence in which jobs are considered for release from the backlog is determined by the schedule of the drum, which also determines in which order jobs are processed or dispatched on the shop floor. In the DBR literature, the focus is on the urgency of jobs and the same procedure is used both for backlog sequencing and dispatching. In this study, we explore the potential of using different combinations of rules for sequencing and dispatching to improve DBR performance. Based on controlled simulation experiments in a pure and general flow shop we demonstrate that, although the original procedure works well in a pure flow shop, it becomes dysfunctional in a general flow shop where job routings vary. Performance can be significantly enhanced by switching from a focus on urgency to a focus on the shortest bottleneck processing time during periods of high load.     

Workload control in job shops with re-entrant flows: an assessment by simulation

One of the key functions of Workload Control is order release. Jobs are not released immediately onto the shop floor – they are withheld and selectively released to create a mix of jobs that keeps work-in-process within limits and meet due dates. A recent implementation of Workload Control’s release method highlighted an important issue thus far overlooked by research: How to accommodate re-entrant flows, whereby a station is visited multiple times by the same job? We present the first study to compare the performance of Workload Control both with and without re-entrant flows. Simulation results from a job shop model highlight two important aspects: (i) re-entrant flows increase variability in the work arriving at a station, leading to a direct detrimental effect on performance; (ii) re-entrant flows affect the release decision-making process since the load contribution of all visits by a job to a station has to fit within the norm. Both aspects have implications for practice and our interpretation of previous research since: (i) parameters given for work arriving may significantly differ from those realised; (ii) increased workload contributions at release mean that prior simulations may have been unstable, leading to some jobs never being released.     

Reducing feedback requirements of workload control

The workload control concept is known as a robust shop floor control concept. It is especially suited for the dynamic environment of small- and medium-sized enterprises (SMEs) within the make-to-order sector. Before orders are released to the shop floor, they are collected in an ‘order pool’. To make the release decision, information regarding the actual situation on the shop floor is required. Within SMEs, this information is often incomplete, incorrect or delayed. However, the workload control approaches discussed in the literature assume precise feedback information. The paper discusses the opportunities for information feedback from the shop floor for centralized order release within SMEs and analyses the information requirements of workload control approaches. These approaches are adapted based on more realistic assumptions regarding information supply within SMEs. The different approaches are compared and assessed by a simulation study. Results show that additional investments in more accurate information supply lead to decreasing marginal improvements in overall shop performance. Additionally, they indicate that the choice of the right workload control approach might have important effects on performance.     

Load smoothing with feedback in a bottleneck job shop

Most of the past research on job shop scheduling has assumed the shop environment where the load-smoothing function in the production planning and control system is ignored and consequently no visibility is provided to the shop. In practice, some kind of load-smoothing is used to smooth the work load level of the shop across the periods, by pulling jobs forward or pushing jobs back. In this study, three load-smoothing approaches with two levels of control for each approach are proposed and tested with two order review/release decisions in a bottleneck job shop. No smoothing becomes a benchmark. Also, the effectiveness of a feedback loop between load-smoothing and the shop floor is investigated. Experiments were conducted in a six-machine job shop simulation model. Results showed that the employment of load-smoothing is important, and pulling jobs forward in a valley period is better than pushing back jobs in a peak period. Controlling the release of jobs to the shop floor in the order review/release phase, given the amount of jobs to be processed during the planning period, is not effective. Also, the feedback system between the planning phase and shop floor to maintain the minimum shop load becomes much more important than simply controlling job release time.     

A method combining rules with genetic algorithm for minimizing makespan on a batch processing machine with preventive maintenance

This paper considers the problem of minimising makespan on a single batch processing machine with flexible periodic preventive maintenance. This problem combines two sub-problems, scheduling on a batch processing machine with jobs’ release dates considered and arranging the preventive maintenance activities on a batch processing machine. The preventive maintenance activities are flexible but the maximum continuous working time of the machine, which is allowed, is determined. A mathematical model for integrating flexible periodic preventive maintenance into batch processing machine problem is proposed, in which the grouping of jobs with incompatible job families, the starting time of batches and the preventive maintenance activities are optimised simultaneously. A method combining rules with the genetic algorithm is proposed to solve this model, in which a batching rule is proposed to group jobs with incompatible job families into batches and a modified genetic algorithm is proposed to schedule batches and arrange preventive maintenance activities. The computational results indicate the method is effective under practical problem sizes. In addition, the influences of jobs’ parameters on the performance of the method are analyzed, such as the number of jobs, the number of job families, jobs’ processing time and jobs’ release time.     

The production capacity of job shops with limited storage space

Suppose the number of jobs which can be stored in front of the machines in a job shop is limited. As a result, arriving jobs for which there is no space in the shop will form a shop queue. The production capacity or maximum departure rate of jobs from the shop will depend on the way in which jobs are selected from the shop queue for release to the machine queues. For a job shop with two identical machines and random routing of jobs a number of release rules are compared. It is shown that the production capacity is increased when the number of jobs in the shop is kept less than the available storage space. Among release rules independent'of job processing times and number of operations the optimum release rule is shown, using dynamic programming, to be the idle machine rule, i.e. only release a job to the shop when a machine would otherwise be idle.     

The impact of advancing due dates in a pure job shop

The effect on shop performance of granting customer requests for setting earlier clue dates on jobs already in process in the shop was investigated, via computer simulation, for a five-machine pure job shop. One-replicate, two-way classification (with interaction) and contrasts were used to examine the effect on various measures of shop performance of (1) four levels of mean interarrival time, A, and (2) five levels of the percentage of all jobs with CKEDD (customer requested earlier due date) status, T. Regression equations were developed for each performance measure in terms of the independent variables, A and T.     

Card-based delivery date promising in pure flow shops with order release control

Card-based systems are simple, effective means of controlling production. Yet most systems concentrate on controlling the shop floor. They neglect other planning tasks, like estimating short, feasible due dates during customer enquiry management. A card-based version of the workload control concept for job shops – COBACABANA (COntrol of BAlance by CArd-BAsed Navigation) – was proposed in the literature to overcome this shortcoming. COBACABANA uses cards for due date setting and order release, making it a potentially important solution for small shops with limited resources. But many such firms operate as flow shops rather than job shops. Research demonstrated that COBACABANA’s release mechanism must be adapted if applied to a pure flow shop, but its approach to due date setting has not been evaluated in such an environment. We show COBACABANA has the potential to improve pure flow shop performance, but its due date setting procedure should be adapted compared to job shops. In a flow shop, due date estimation can also be further simplified by considering the load awaiting release to the first (gateway) station only while maintaining most performance benefits. The results are important for all card-based systems that aim to stabilise work-in-process, including kanban and ConWIP (Constant Work-in-Process).     

Priority scheduling with cost considerations

Although many articles have been published on the general priority scheduling problem, very few have been concerned with directly minimizing costs. The few studies which do consider overall costs do not use these costs in establishing a job's priority in the queue. This paper investigates how the time and cost performance of jobs are affected by the use of a rule which directly considers costs. A simulation model of a hypothetical job shop is used to examine several of these cost rules, as well as some common rules concerned with the timeliness of jobs. Performance measures include both time-oriented and cost-oriented measures. The results indicate that rules which directly consider costs (or profit) may prove practical for a manager where minimization of WTP and maximization of ROT are the primary and secondary objectives of the company     

Family based dispatching in manufacturing networks

Intrinsic to family based dispatching is the grouping of similar types of jobs in front of a machine for joint processing. Machine flow times may be improved in this way, as less time is spent on set-ups. Our observations in practice, however, suggest that family based dispatching may result in a bulky arrival pattern for successor manufacturing stages, thereby causing additional delay. So far, literature seems to neglect this effect. To explore this issue we develop queuing theoretical approximations of flow times for a simple two-stage shop. It appears that the optimal batch size for the shop is typically smaller than the optimal batch size for the batch machine. Furthermore, we propose extensions to existing dispatching rules by using information on successor stages. Existing and new extended rules are tested by an extensive simulation study. In line with the queuing theoretical analysis the outcomes indicate that exhaustive rules – assuming batch size to be equal to family queue length – are clearly outperformed by non-exhaustive rules – allowing for smaller batches. Moreover, results show that the inclusion of local information on successor stages in rule decision making improves shop flow times.     

Comparison of dispatch policies for a single server queueing model with limited operational control

In this paper we consider a single server queueing model for a single machine dynamic job shop in which shop level scheduling is not permitted. External arrivals of jobs are received in a dispatch area from which their release to the job shop is controlled. To overcome the limitation of operational control, we propose three different dispatch policies and compare their performances to that of a first come first served dispatch policy. The four dispatch policies considered are (1) first come first served, (2) scheduling within generations, (3) scheduling within periodic review, and (4) scheduling within fixed batch sizes.     

Workload control release mechanisms: from practice back to theory building

Much Workload Control research has focussed on the order release stage but failed to address practical considerations that impact practical application. Order release mechanisms have been developed through simulations that neglect job size variation effects while empirical evidence suggests groups of small/large jobs are often found in practice. When job sizes vary, it is difficult to release all jobs effectively—small jobs favour a short period between releases and a tight workload bounding while large jobs require a longer period between releases and a slacker workload bounding. This paper represents a return from a case study setting to theory building. Through simulation, the impact of job sizes on overall performance is explored using all three aggregate load approaches. Options tested include: using distinct load capacities for small/large jobs and prioritising based on job size or routing length. Results suggest the best solution is assigning priority based on routing length; this improved performance, especially for large jobs, and allowed a short release period to be applied, as favoured by small jobs. These ideas have also been applied to a second practical problem: how to handle rush orders. Again, prioritisation, given to rush orders, leads to the best overall shop performance.     

Integrating load-based order release and priority dispatching

Workload control (WLC) is a well-established production control concept for job shops that put primary emphasis on load-based order release. Recent advances in load-based order release research have led to an improved delivery performance at reduced shop floor workloads. But although order release is the primary focus of WLC research, it must be coupled with priority dispatching on the shop floor if order progress is to be regulated. Prior simulation research suggests that load-based order release methods should only be coupled with simple dispatching rules because other, more powerful rules can conflict with the functioning of the release method. Yet, recent empirical research suggests that powerful priority dispatching rules – such as due date-oriented dispatching rules – are in fact needed for a high level of delivery performance to be obtained in practice. This paper focuses on overcoming the conflict between order release and dispatching, so load-based order release can be combined with due date-oriented dispatching. Preliminary analysis reveals that part of the conflict is because existing due date-oriented dispatching rules overcompensate for schedule deviations that occur when orders are either released earlier or later than planned. Two alternative new dispatching rules based on an improved method of determining operation due dates are then developed to better account for schedule deviations and overcome the conflict with load-based order release. Further improvements in delivery performance are obtained, while the large workload reductions achieved by recently developed load-based order release methods are retained.     

A methodology for planning and controlling workload in a job-shop: a four-way decision-making problem

There has been extensive research on workload and input–output control with the objective of improving manufacturing operations in job-shops. In this paper, a multiple decision-making scheme is proposed to plan and control operations in a general job-shop, and to improve delivery and workload related performance measures. The job-shop characteristics reinforce the need for designing a global system that controls both the jobs entering (order acceptance, due date setting and job release) and the work-in-process (dispatching), leading to an improvement of operational measures. Previous research has concentrated on scheduling a set of orders through the shop floor, according to some decision mechanism, in order to optimise some measure of performance (usually total lead time). This means that, since only a part of the decision-making system is being optimised, the resulting decision may be sub-optimal. In this paper it is shown that the performance of the different decision rules changes when they are considered simultaneously. Hence, a higher level approach, where the four decisions (order acceptance, due date setting, job release and dispatching) are considered at the same time, should be adopted to improve job-shop operational performance.     

An effective heuristic for adaptive control of job sequences subject to variation in processing times

Variation in sequential task processing times is common in manufacturing systems. This type of disturbance challenges most scheduling methods since they cannot fundamentally change job sequences to adaptively control production performance as jobs enter the system because actual processing times, are not known in advance. Some research literature indicates that simple rules are more suitable than algorithmic scheduling methods for adaptive control. In this work, a ‘state space – average processing time’ (SS-APT) heuristic is proposed and compared to four most commonly used scheduling rules and two well-established heuristics based on Taillard’s benchmarks. It is shown that the adaptive control is made possible under variation in processing times given the flexibility and strong performance of the SS-APT heuristic, especially for work-in-process inventory control.     

Alternative order release mechanisms: a comparison by simulation

Releasing mechanisms are the set of rules which determine when matured orders i.e. those confirmed orders for which materials and tools are available, are dispatched to the shop floor so that processing can commence. This paper presents a simulation in which three such mechanisms are compared with a scenario in which matured orders are automatically released. Two of the mechanisms assume that the set of jobs to be released is given and that capacity cannot be adjusted. In contrast, the third rule allows capacity to be adjusted both as new jobs enter the system and as they are released to the shop floor. The simulation study shows that the latter rule is the best releasing rule under delivery performance and workload measures, but is slightly worse under the workload balance measure. This high performance is achieved at a relatively low cost in terms of increased capacity. In comparison with a scenario in which mature orders are automatically released to the shop, the latter rule performs better under all criteria except the proportion of tardy orders. It is concluded that further research is needed to show whether order release mechanisms can improve all delivery criteria as well as workload criteria.     

Implementing a loading heuristic in a discrete release job shop

The scheduling literature has developed two almost mutually exclusive problems; a static and a dynamic scheduling problem. The result has been that different tools have been developed to solve each problem. In this research, a model is developed such that it contains elements of both the static and the dynamic problems. This model, called here the discrete release model, considers the routing, loading, and release decisions as well as the customary sequencing decision evident in most job shop research. The objective of the research is to implement a method for examining tentative loading assignments prior to their release to the shop floor.

The research develops a single pass, sequential routing and loading system. A heuristic is then developed that will enable jobs to be reloaded and rerouted prior to their start of processing. The system is tested in various shop environments to ascertain the effectiveness of this loading heuristic.     

Family based dispatching with batch availability

Family based dispatching rules seek to lower set-up frequencies by grouping (batching) similar types of jobs for joint processing. Hence shop flow times may be improved, as less time is spent on set-ups. Motivated by an industrial project we study the control of machines with batch availability, i.e. all the jobs of the same batch become available for processing and leave the machine together. So far the literature seems to have neglected this type of shop by restricting its focus on machines with item availability, i.e. assuming machine operations concern single jobs. We address this gap by proposing extensions to existing family based dispatching rules. Extended rules are tested by an extensive simulation study. Best performance is found for non-exhaustive rules, which allow for alternative choices of batch size. Performance gains are highest for low set-up to run-time ratios and/or high workloads.