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Order release optimisation is essential in production planning, especially in discrete manufacturing. Order release planning models with load-dependent lead times must anticipate the time-dependent work-in-process and output for any given release schedule and thus require an anticipation model that approximates the time-dependent behaviour of queueing systems. We present a generic optimisation model for order release planning in stochastic, non-stationary manufacturing systems that includes a well-defined interface for the anticipation model. We develop two stationary backlog carryover (SBC) approaches to approximate time-dependent queueing behaviour and prove their consistency with the order release model. The resulting nonlinear programming model is shown to be a special case of the well-known clearing function models. A numerical study demonstrates that the optimised order releases for different demand patterns are close to the optimum that results from simulation-based optimisation even for extreme demand and release patterns. The resulting output closely matches the simulated output with some deviations. [ABSTRACT FROM AUTHOR]

This paper shows the effectiveness of labour transfers in addressing premature idleness caused by controlled order release. Controlled order release restricts order entry to the shop floor and is commonly employed in high-variety manufacturing where it results in benefits such as stable work-in-progress. However, it can increase waiting times when orders are blocked from release, while capacities are idling. This issue, known as premature idleness, negatively impacts delivery performance. Previous studies have primarily focused on addressing premature idleness through input control by releasing new orders to idling workstations. This approach overlooks the potential of output control during premature idleness, transferring labour to assist at other workstations in a dual resource constrained setting. Using simulation, this study demonstrates that output control significantly improves delivery performance—in terms of mean tardiness and percentage tardy—and reduces total and shop floor throughput times. Importantly, this result proves robust, even when the efficiency of the assisting worker is severely limited. Shop-level performance improves despite the efficiency loss of the worker. The impact of the where-rule is minimal, while the efficacy of the priority dispatching rule depends on the joint efficiency of collaborating workers. Finally, we show that combining input control and output control enhances performance, providing opportunities for further research on the role of both control approaches in high-variety manufacturing. [ABSTRACT FROM AUTHOR]

In manufacturing shops in practice, machine capacity is often constrained by more than one type of resource. Yet research mainly focusses on the effects of only one type of resource that constrains machine capacity, e.g. labour, tooling or auxiliary constraints. In response, we use simulation to assess the impact of order release, dispatching and resource assignment rules in make-to-order job shops with multiple resource constraints. The capacity wasted while a machine stands idle waiting for other resources increases with the number of constraints, and all three production planning and control functions have little impact on this waiting time. Effective production planning and control can however improve operational performance in terms of time and tardiness-related measures. In general, combining order release control with a dispatching rule that prioritises jobs for which all resources are available at dispatching and a longest queue resource assignment rule leads to the best performance. Most importantly, and rather counterintuitively, prioritising orders with the fewest missing resources worsens the performance of both the dispatching and resource assignment rule since it reduces resource utilisation during periods of high load. Results from dual resource-constrained shops are consequently not directly transferable to more complex resource-constrained shops. [ABSTRACT FROM AUTHOR]

Workload Control withholds orders from the shop floor in a backlog from which they are released to meet certain performance metrics. This release decision precedes the execution of orders at shop floor stations. For each station there are consequently three types of workload: indirect, released work that is still upstream of the station; direct, work that is currently at the station; and, completed, work that is still on the shop floor but is downstream of the station. Most release methods control an aggregate workload made up of some representation of at least two of these three workload types. Yet the core objective of Workload Control release methods relates to only one of the three types – that is, to create a small, stable direct load in front of each station. Clearly, order release would be greatly simplified if only the direct load had to be considered. Using discrete event simulation, we show that Direct Workload Control leads to performance levels that match those of more complex and sophisticated approaches to Workload Control. Further, it greatly simplifies continuous order release, decentralising the release decision by allowing it to be executed at each gateway station. This has important implications for research and practice. Highlights Presents a new Workload Control release method that controls the direct load only. The new method significantly simplifies workload calculations. The new method can be decentralised with control exercised locally at gateway stations. Simulation results demonstrate comparable performance to more sophisticated methods. The new method improves the performance of large jobs. [ABSTRACT FROM AUTHOR]

Production planning and control (PPC) systems are important to the competitiveness of manufacturing firms and their ability to benefit from recent technological advances. We give an overview of research and unsolved research questions in PPC systems related to the order release function that sets output targets for autonomous production units that manage production at the shop-floor level. We describe the hierarchical Manufacturing Planning and Control (MPC) and Advanced Planning and Scheduling (APS) architectures for PPC systems prevalent in practice and the positioning of the order release task within these frameworks. We then describe the research streams relevant to order release, optimisation models for order release planning, and the relation of these models to the overall PPC system. Modelling the dynamic response of production units to time-varying work input, which represents an extension of classical production theory by incorporating the time dimension, is identified as the major modelling challenge. We conclude by suggesting several unsolved research questions that should encourage researchers to work on this topic which is far from mature. [ABSTRACT FROM AUTHOR]

An essential task in manufacturing planning and control is to determine when to release orders to the shop floor. A prominent approach is the workload control (WLC) concept which originated from the idea of controlling flow times by controlling order releases. Despite recent advances in rule based WLC models, the recent semiconductor literature has neglected them, although it has been shown that they outperform most other periodic and continuous order release models. Therefore, we adapt the most successful rule based WLC model, the LUMS-COR approach and compare it with two approaches from the semiconductor manufacturing literature: Starvation Avoidance (SA) and ConLOAD approach. We include three pool sequencing rules, namely First-Come First-Served (FCFS), Earliest Due Date (EDD) and Critical Ratio (CR). We analyse their performance using a simulation model of a scaled-down wafer fabrication facility. The results show that, in comparison to the other two order release approaches, the LUMS-COR model yields lower total costs due to a more balanced shop and better timing performance which is robust across different settings. This suggests that the adapted LUMS-COR model has high potential to become a viable alternative to the rule based order release mechanisms used in semiconductor industry to date. [ABSTRACT FROM AUTHOR]

Additive Manufacturing (AM) shops typically produce high variety, low volume products on a to-order basis. Products are first created in parallel batches at a single AM station before being subjected to several post-processing operations. While there exists an emerging literature on AM station scheduling and order book smoothing, this literature has largely neglected downstream post-processing operations, which also affect overall performance. Workload Control provides a unique production control solution for these post-processing operations, but the specific AM shop structure has been neglected in the literature. Using simulation, this study shows that load balancing via the use of workload norms, as is typical for Workload Control, becomes ineffective since the norm must allow for the operation throughput time at the AM station and for its variability. A sequencing rule for the jobs waiting to be released that inherently creates a mix of jobs that balances the workload is therefore identified as the best-performing rule. These findings reinforce the principle that load limiting should be used at upstream stations whereas sequencing should be applied at downstream stations. Finally, although the focus is on AM shops, the findings have implications for other shops with similar structures, e.g. in the steel and semi-conductor industries. [ABSTRACT FROM AUTHOR]

An essential task in manufacturing planning and control is to determine when to release orders to the shop floor. One key parameter is the lead time which is the planned time that elapses between the release of an order and its completion. Lead times are normally determined based on the observed time orders previously took to traverse the production system (flow times). Traditional order release models assume static lead times, although it has been shown that they should be set dynamically to reflect the dynamics of the system. Therefore, we present a flow time estimation procedure to set lead times dynamically using an artificial neural network. Additionally, we implement a safety lead time to incorporate the underlying cost ratio between finished inventory holding and backorder costs in the order release model. We test our proposed approach using a simulation model of a three-stage make-to-order flow-shop and compare the forecast accuracy and the cost performance to other forecast-based order release models from the literature. We show that our proposed model using artificial neural networks outperforms the other tested approaches, especially for scenarios with high utilisation and high variability in processing times. [ABSTRACT FROM AUTHOR]

Most manufacturing shops in practice have limited physical space in front of each workstation, due, for example, to physical, economical or operational constraints. As a result, a job may cause blocking because it has to remain at a given station after an operation has been completed until space in front of the next station in its routing becomes available. Despite this practical reality, the Workload Control literature typically assumes infinite buffer limits and therefore neglects the impact of blocking. Using simulation, we highlight the direct, detrimental impact of blocking in both the pure and general flow shop. Workload Control order release dampens the effect of blocking and improves overall performance. This makes Workload Control order release even more important in the context of shops with blocking or physical space constraints. Further analysis reveals that the impact of blocking is less pronounced in the pure flow shop given its directed routing. Finally, most of the blocking that occurs is because jobs cannot enter the shop, i.e. there is no space in front of the gateway station. This re-emphasises the close relationship between blocking and release methods that limit the workload, and it highlights the importance of workload balancing. [ABSTRACT FROM AUTHOR]

An important goal of Production Planning and Control systems is to achieve short and predictable flow times, especially where high flexibility in meeting customer demand is required, while maintaining high output and due-date performance. One approach to this problem is the workload control (WLC) concept. Within WLC research two directions have been developed, largely separately, over time: Rule based and optimisation-based models. If a company intends to introduce an order release concept based on WLC it first has to decide which of these two approaches should be applied. Therefore, this paper compares two of the most widely used and considered best performing periodic order release models out of both streams: the LUMS (rule based) and the clearing function model (optimisation based). The parameters of both approaches are set using simulation optimisation. The performance is compared using a simulation study of a hypothetical job shop in a rolling horizon setting. The results show that the optimisation model outperforms the rule-based mechanism in all instances with stochastic demand (exponential inter-arrival times), but is outperformed in aggregate cost of backorders and inventory holding and balancing measures by the LUMS approach for scenarios with high utilisation and seasonal demand. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Order release is a key production planning and control function, specifically in high variety contexts. A large literature on release methods that balance the workload consequently emerged. These Workload Control methods can be rule based, using a simple greedy heuristic, optimization based or optimization based with lead times that are exogenous. Although all three types of methods have the same objective, their performance has never been compared. Using simulation, this study shows that a better on time delivery performance of jobs can be achieved by the two optimization based release methods. Most importantly, optimization based methods that assume lead times to be exogenous significantly outperform alternative methods in terms of tardiness performance. Rule based and optimization based Workload Control without exogenous lead times overemphasize average lateness reduction, which leads to sequence deviations that offset performance improvements through balancing. In contrast, Workload Control methods that assume lead times to be exogenous limit sequence deviations, which leads to a significant reduction in dispersion of lateness. This has important implication for the future design of order release methods, and managerial practice. [ABSTRACT FROM AUTHOR]

Most Workload Control literature assumes that delivery performance is determined by tardiness related performance measures only. While this may be true for companies that directly deliver to end-customers, for make-to-stock companies or firms that are part of supply chains, producing early often means large inventories in the finished goods warehouse or penalties incurred by companies downstream in the supply chain. Some earlier Workload Control studies used a so-called time limit, which constrains the set of jobs that can be considered for order release, to reduce earliness. However, recent literature largely abandoned the time limit since it negatively impacts tardiness performance. This study revisits the time limit, assessing the use of different adaptive policies that restrict its use to periods of either low or high load. By using a simulation model of a pure job shop, the study shows that an adaptive policy allows to balance the contradictory objectives of delaying the release of orders to reduce earliness and to release orders early to respond to periods of high load as quick as possible. Meanwhile, only using a time limit in periods of high load was found to be the best policy. [ABSTRACT FROM AUTHOR]

Workload Control is a production control concept for high-variety shops built on the principle of input/output control. The literature, however, has argued that input/output control overemphasises throughput improvements to the detriment of the timing of individual orders and, consequently, that it needs to be supplemented by a preceding customer enquiry stage where due dates are set. Yet, although there are broad separate literature streams on due date setting, order release, and output control, there is a lack of research on the three functions together. In response, this study uses simulation to assess the combined performance effect of all three functions. Results show that each control function can be related to a specific performance objective. The degree of emphasis that should be placed on each function, therefore, depends on a company's specific performance needs. Due date setting and capacity adjustments (output control) are shown to support each other as they address different performance objectives. Meanwhile, order release (input control) is effective in reducing work-in-process and can play a role in making throughput improvements when capacity adjustments are not possible. Findings enhance existing literature on the diagnosis of delivery reliability performance in high-variety shops, with important implications for research and practice. [ABSTRACT FROM AUTHOR]

Workload Control (WLC) seeks to align capacity with demand, where capacity is typically assumed to be restricted by a single constraint - machine capacity. In practice, however, shops are often restricted by dual resource constraints: labour and machines. This study, therefore, uses simulation to investigate the performance of WLC in Dual Resource Constrained (DRC) high-variety shops with fully interchangeable labour. By considering several environmental factors and different labour assignment and dispatching rules, it is demonstrated that the order release function of WLC maintains its positive impact on performance in a DRC shop under different staffing levels. The positive effect of considering labour availability at release, as proposed in previous research, could not, however, be confirmed. Thus, the original release method can be applied if labour is fully interchangeable. In terms of labour assignment, we show that a distinct assignment pattern that differs between upstream and downstream stations improves performance if the routing is directed. Meanwhile, dispatching plays a less important role but creates important interaction effects with the assignment rule. Finally, the results suggest that increasing the service rate is a better response to the reduction in capacity that results from labour absenteeism than lowering the input frequency of work. [ABSTRACT FROM AUTHOR]

Kanban systems are simple yet effective means of controlling production. Production control is decentralised or exercised locally on the shop floor, i.e. a downstream station signals to an upstream station that an item is needed. If items are always the same and known, then demands can be satisfied instantaneously from stock; but if items differ and are unknown, demands must first be propagated backwards from station to station before being satisfied. The former is defined as an inventory control problem and the latter as an order control problem. Handling the order control problem via kanban involves a decentralised card acquisition process (during which information is propagated from station to station) that is separated from the actual production process. COBACABANA (control of balance by card-based navigation), an alternative card-based solution, shares kanban's control structure but centralises the card acquisition process. Evaluating the two systems therefore provides a unique opportunity to compare decentralised and centralised control. Using simulation, we demonstrate that it is specifically the centralised card acquisition process that allows COBACABANA to balance the workload across resources and thus to outperform kanban in an order control problem. This has major implications for research and practice. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

When order release is applied, jobs are withheld in a backlog from where they are released to meet certain performance targets. The decision that selects jobs for release is typically preceded by a sequencing decision. It was traditionally assumed that backlog sequencing is only responsible for releasing jobs on time, whereas more recent literature has argued that it can also support load balancing. Although the new load-based rules outperform time-based rules, they can be criticized for requiring workload information from the shop floor and for delaying large jobs. While some jobs will inevitably be delayed during periods of high load, we argue that this delaying decision should be under control of management. A simulation study of a wafer fab environment shows that a time-based rule matches the performance of more complex load-based backlog sequencing rules that have recently emerged. The new rule realizes the lowest percentage of tardy jobs if the lower bound that distinguishes between early and urgent jobs is set appropriately. It provides a simpler means of improving release performance, allowing managers to delay jobs that have adjustable due dates. [ABSTRACT FROM AUTHOR]

This paper deals with improving the lead-time performance of a large crystal manufacturer that uses a state-of-the-art commercial Enterprise Resource Planning system. Since the company encountered some limitations of the standard production planning and control (PPC) system it sought for improvements by implementing an order release mechanism based on workload control (WLC). WLC employs certain rules for releasing orders in order to maintain a certain level of work in process to achieve a certain utilisation of the production system and thus control the flow times in order to meet the required due dates of the orders. We describe the successful implementation of an order release mechanism based on the WLC concept in this make-to-stock company. The paper describes the implemented order release mechanism, the implementation process and its impact on the company’s performance. We show that the core function of WLC - the order release mechanism - can be integrated successfully into an existing PPC system. Furthermore, this study highlights the applicability of WLC to a wider range of companies, especially to make-to-stock manufacturers. [ABSTRACT FROM AUTHOR]

Lot-to-order matching (LTOM) is a crucial process in semiconductor manufacturing since inefficient allocation and order release have strong adverse effects on factory performance. Although prior research proposes several heuristics for the mathematical optimization of the LTOM process, successful real-world implementations following practical and comprehensive approaches are scarce. Our longitudinal case study addresses that issue by summarizing the results of an extensive research project on the automation and optimization of the LTOM process for 200 mm and 300 mm wafers at Infineon Technologies Dresden. Grounded in Action Design Research, we integrated different research methods to provide meaningful insights into the benefits, challenges, and best practices of our approach. Thereby, we also compare the results for 200 mm and 300 mm wafers. The project had positive impacts on multiple quantitative and qualitative key performance indicators, e.g., throughput, on-time delivery, tool utilization, cycle and working time savings, collaboration, and employee satisfaction. Finally, we provide managerial guidance for similar projects and implications for future research. [ABSTRACT FROM AUTHOR]

The demand for customer-specific product variants leads to a shift to job shop production, in which order scheduling takes a mayor role to increase logistical target values without ad-hoc interventions into the running production. Agent applications, e.g. combinations of reinforcement learning (RL) and simulation, are promising solutions to solve the scheduling problem. This paper designs a methodology for automating the order release decision of real production scenarios by applying a RL agent, which has been trained on an application-specific simulation model. By an integrated validation unit the performance can be measured against known order release strategies. [ABSTRACT FROM AUTHOR]

The operational quality and reliability of a manufacturing system is greatly influenced by uncertain or variable environments, therefore robustness is one of the most important indicators for measuring the operational quality of the non-repetitive dynamic manufacturing system. Controlling the order release to limit work in process at a stable level and protect throughput from variation is crucial to achieving robustness of manufacturing system performance. To deal with the influences of bottleneck severity and variable resource on system performance, a refined order release method is presented, which releases order periodically based on the corrected aggregate load and continuously based on the bottleneck buffer load. The operational quality of this method with the classical order release method under non-repetitive dynamic manufacturing system is compared by modeling and simulation. The results show that the refined order release method is more robust for general flow shop with higher protective capacity and resource variability. [ABSTRACT FROM AUTHOR]

The construction of large maritime structures requires the manufacture of higher order assemblies. A large number of components with different machining processes and different production sequences make it difficult to coordinate the overall process. In addition, high and long-lasting customer influence and continuous iteration loops mean that product adjustments are made repeatedly. Furthermore, the mostly manual manufacturing processes are difficult to calculate due to the uniqueness of many products in the maritime sector. Insufficient orchestration of the processes disrupts the flow of materials. Especially the integration of modified components is associated with an increased control effort. Longer waiting and throughput times are the result. In this article, the potential of optimized order release with a focus on constructively modified components is demonstrated with the help of comprehensive digitalization. In this context, the development of mechanisms for optimized scheduling plays an overriding role. In this respect, the special features of make-to-order production are the subject of the considerations. The characteristics allow specific control methods, but at the same time pose challenges for process design. Evaluations with regard to practical use provide information about the potential possibilities and the frequencies of taking action. The consequences of the action steps are also part of the present investigations. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM PUBLISHER]

In many real-life high-variety make-to-order shops, jobs are physically transported from one station to another, and transportation capacity may constrain order progress on the shop floor. Yet, the material handling literature on vehicle assignment rules remains largely inconclusive on which rule to apply, and it neglects order release control. Similarly, and despite the importance of material handling, its impact is widely neglected in the order release literature. In response, this study assesses the combined performance effect of vehicle assignment, order release and dispatching rules. It uses discrete event simulation. Results show that assigning a vehicle to the station with the largest outgoing queue leads to the best performance. This simple vehicle assignment rule has been largely neglected in the literature since the 1980s. In contrast, the two rules that have received the most attention in the literature – the shortest distance and first-come-first-served rules – lead to the worst performance. Meanwhile, order release has a direct detrimental performance effect in pure job shops with material handling constraints. This identifies an important contingency factor so far neglected in the literature that assesses the applicability of order release. More specifically, the use of order release should be restricted to general flow shops with more directed routings since, in these contexts, it can reduce throughput times without jeopardizing tardiness performance. [ABSTRACT FROM AUTHOR]

The workload control literature highlights the importance of balancing the shop floor workload, but also acknowledges that this can conflict with processing the most urgent orders – hence, there is a trade-off. In practice, shops contain many complexities, e.g. simultaneous batching and sequence-dependent set-up times that may conflict with processing the most urgent orders and require other solutions than workload balancing to avoid capacity losses. This adds to the trade-off dilemma, which traditionally only considers timing and balancing. This paper develops a framework that determines whether to address a complexity through order release or dispatching. It comprises two dimensions: (i) the typical position of a complexity in the routing of an order and (ii) the criticality of the complexity. A case study is presented, which demonstrates the framework’s utility and illustrates the development of specific solutions designed to handle the complexities. Most complexities present in the case require handling at the order release stage. The challenges of handling multiple complexities at this decision level are evaluated. Finally, the implications for managers and future research are outlined. [ABSTRACT FROM PUBLISHER]

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. [ABSTRACT FROM PUBLISHER]

When order release is applied, jobs are withheld in a backlog from where they are released to meet certain performance targets. The decision that selects jobs for release is typically preceded by a sequencing decision. It was traditionally assumed that backlog sequencing is only responsible for releasing jobs on time, whereas more recent literature has argued that it can also support load balancing. Although the new load-based rules outperform time-based rules, they can be criticized for requiring workload information from the shop floor and for delaying large jobs. While some jobs will inevitably be delayed during periods of high load, we argue that this delaying decision should be under control of management. A simulation study of a wafer fab environment shows that a time-based rule matches the performance of more complex load-based backlog sequencing rules that have recently emerged. The new rule realizes the lowest percentage of tardy jobs if the lower bound that distinguishes between early and urgent jobs is set appropriately. It provides a simpler means of improving release performance, allowing managers to delay jobs that have adjustable due dates.

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. [ABSTRACT FROM PUBLISHER]

Workload control (WLC) has been developed as a production planning and control approach for job shop manufacturing. By balancing loads across work centres, WLC anticipates the fact that multiple work centres may become potential bottlenecks in the short term. This approach is generally tested in job shop models that assume equal utilisation levels for all work centres, which will create maximum bottleneck shiftiness. However, job shop practice clearly shows differences in utilisation levels, which means that some work centres can be seen as non-bottlenecks, having protective capacity. This study investigates the effect of different levels of protective capacity on the performance of state-of-the-art WLC release methods. More in detail, it shows how the level of protective capacity interacts with the influence of workload norms at work centres. Despite the fact that WLC has been developed for highly balanced utilisations, results indicate that WLC could also be effective in unbalanced situations. However, norm setting requires careful attention. Disregarding the norms of non-bottleneck work centres, a common sense approach, might strongly deteriorate performance when the level of protective capacity is not sufficiently high. Contrarily, tighter norms for non-bottleneck work centres are shown to perform better in this situation. [ABSTRACT FROM PUBLISHER]

Be it teaching or discussing logistic target attainment with practitioners, there is often a confusing gap between the manufacturing control methods applied on the one hand and the logistic objectives on the other hand. Which method is appropriate to increase on-time delivery, which to decrease the WIP? When configuring manufacturing control the discussion often quickly turns to choosing one method over the other and too often the results are disappointing. In order to provide a framework for a more systematic approach, a model has been developed that links the tasks of manufacturing planning and control with the logistic objectives. [ABSTRACT FROM PUBLISHER]

In this paper, we report a simulation study on the role of sequence-dependent set-up times in decision making at the order release level of a workload controlled make-to-order flow-shop. The study evaluates the potential for set-ups savings, dependent on the level of workload in the shop, for two alternative strategies, namely considering set-up times centrally, within the release decision or locally, within the dispatching decision. These strategies are compared and assessed on the basis of two main performance measures namely time in system and standard deviation of the job lateness. Results indicate that the local strategy, which has been traditionally adopted in practice and in most of the studies dealing with sequence-dependent set-up times, does not always give the best results. The release frequency and the shop workload appear critical to the selection of the strategy to adopt, strongly influencing system performance. [ABSTRACT FROM AUTHOR]

Synchronous manufacturing aims at achieving the benefits of intermittent production lines in production situations that operate without lines. Benefits such as short and constant throughput times and predictable capacity loading can be acquired through an appropriate design of the synchronous manufacturing system and its control system. The order release mechanism is an essential part of this control system. It determines the sequence in which orders are released to the shop floor. As orders may differ in the amount and distribution of their capacity requirements over subsequent production stages, total capacity load may vary over time. If the available capacity per period is not flexible, capacity balancing becomes an issue in the order release decision. In practice, heuristics or rules of thumb are used to solve this problem, but their effectiveness is questioned. This paper examines the effectiveness of some new heuristics that are based on insights from assembly system design and work load control, and compare their performance with an optimal solution approach. The approaches are evaluated in a rolling schedule environment, and under different levels of capacity fluctuations and problem sizes. The results show that the performance of the heuristic solutions deteriorates if capacity fluctuations between the stages increase. If we measure both the amount and frequency of shortages over a long period of time in a rolling schedule environment, a quite simple rule that only takes the available capacity during the first stage into account outperforms more intelligent rules. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Updating planned lead times in response to changing workload levels leads to erratic ordering behaviour, resulting in even larger variability in the workload levels and flow times. This phenomenon is called lead time syndrome, and describes the cyclic interaction between adaptive planned lead times and order sizes. Although it has been conceptually defined and intuitively accepted, formal analysis with analytical evaluation of the phenomenon has not been conducted. The objective of this paper is to provide a stronger understanding of the lead time syndrome, and to give new insights into the effects of frequently updating planned lead times. We develop a two-dimensional Markov process to model a single-item production process with orders released sensitive to the planned lead time. Using matrix-geometric methods, analytical results on the utilization level and the variability in the system are presented in relation to the frequency of updating the planned lead time. Although the average utilization level is always retained, the lead time syndrome causes an increase in the average workload level and the actual flow times of the completed orders. The variability of the planned lead time increases with the update frequency except at the utilization boundaries, where the relative effect of the update frequency diminishes. [ABSTRACT FROM AUTHOR]

POLCA (i.e. Paired-cell Overlapping Loops of Cards with Authorization) is a card-based production control approach developed to support the adoption of Quick Response Manufacturing. POLCA's control mechanism is unique since it combines a card-based element (the paired cell overlapping loops of cards) with a higher-level Material Requirements Planning system for release authorization. POLCA has been applied in practice and evaluated in research, but the loops of cards element (POLC) has been adopted without the authorization element (A). In response, we use simulation to evaluate the effect of POLCA's authorization element. We show that this element has a direct detrimental effect on percentage tardy and mean tardiness performance. While the literature argues that the authorization element should be an integral part of POLCA, our results suggest the opposite. This has important implications for research and practice. Instead of using POLCA with its authorization element, it is preferable to combine POLC—the card-based element—with a shop floor dispatching rule. [ABSTRACT FROM AUTHOR]