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Either make-to-order (MTO) or make-to-stock (MTS) alone cannot satisfy the customer demand. Therefore, companies in different sectors are trying to adopt a hybrid MTO-MTS production strategy. Unlike MTO or MTS, there are few research on hybrid MTO-MTS environment and very few considering the operational issues. The workload control seems to handle better the operational issues in the hybrid environment considering job shop configuration whereas drum buffer rope has been designed to handle the bottleneck issue in a pure flow shop. Therefore, the objective of this paper has been defined to compare bottleneck-based release models and load-based ones in a hybrid MTO-MTS flow shop. Simulation results are not clearly in favour of one over the other, since besides severity, there is another important factor to consider: the choice of control at the dispatching level, and its connected trade-offs. In particular, implementing this control with the bottleneck-based rule is effective for MTO performances, especially in cases of high severity. Instead, when control at dispatching is absent, the workload control as a release rule is preferred, leading also to the best lead times for low severity. The results demonstrate important managerial and research implications for bottleneck-based and load-based release models in MTO-MTS flow shops. [ABSTRACT FROM AUTHOR]

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 paradigm shift toward Industry 4.0 is facilitating human capability, and at the center of the research are the workers—Operator 4.0—and their knowledge. For example, new advances in augmented reality and human–machine interfaces have facilitated the transfer of knowledge, creating an increasing need for labor flexibility. Such flexibility represents a managerial tool for achieving volume and mix flexibility and a strategic means of facing the uncertainty of markets and growing global competition. To cope with these phenomena, which are even more challenging in high-variety, low-volume contexts, production planning and control help companies set reliable due dates and shorten lead times. However, integrating labor flexibility into the most consolidated production planning and control mechanism for a high-variety, low-volume context—workload control—has been quite overlooked, even though the benefits have been largely demonstrated. This paper presents a mathematical model of workload control that integrates labor flexibility into the order review and release phase and simulates the impact on performance. The main results show that worker transfers occur when they are most needed and are minimized compared to when labor flexibility is at a lower level of control—shop-floor level—thus reducing lead time. [ABSTRACT FROM AUTHOR]

Most literature on make-to-order shops assumes that service rates are independent of the system state. In practice however, the service rate is often dependent on the workload level experienced by the worker. While a body of knowledge on state-dependent service rates exists, the available literature has not given sufficient attention to make-to-order shops, which are often characterized by complex routings and defined due dates, which means delivery performance becomes a major concern. This study uses simulation to assess the performance impact of state-dependent service rates under different degrees of routing directedness. We show that including information on the load upstream of a station when making service rate adjustments has the potential to improve performance compared to considering the load directly queuing at a station only, as has been the case in previous research on state-dependent service rates. Moreover, using the same threshold to trigger service rate adjustments at each station in shops with directed routings leads to higher service rates at upstream stations. This service rate imbalance can be avoided by using different triggering thresholds for upstream and downstream stations. Further, and most importantly, we show that although speeding up behavior during high load periods significantly improves performance, if worker fatigue leads to a decrease in the service rate in response to the initial increase then performance may in fact deteriorate. [ABSTRACT FROM AUTHOR]