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POLCA is an important card-based control system for low volume, high variety production contexts. A job can only be produced at an upstream station if it has acquired a POLCA card that has returned from its downstream station. A common assumption in the POLCA literature is that cards are allocated to jobs as soon as they return to the upstream station. This dissects the queue in front of a station into jobs that have a card (and can be produced) and those that do not have a card (and cannot be produced). This artificially and prematurely constrains the dispatching decision, i.e. the decision concerning which job to produce next at a station. In response, this paper proposes integrating the card-allocation and dispatching decisions such that the allocation of POLCA cards to jobs is postponed until the dispatching decision is made. Simulation results demonstrate that this integrated approach does not improve performance under simple ERD dispatching, as is commonly applied in the POLCA literature. But when a more powerful rule is applied, percentage tardy and mean tardiness performance improve by more than 75% and 50%, respectively, for an integrated decision. Most importantly, results suggest that in production environments like the one considered in this study, the integrated approach dispenses with the use of POLCA altogether if a suitable priority rule is used.

Material Flow Control (MFC) mechanisms control the movement of jobs through a set of stationery capacity resources on the shop floor. Although the objective of MFC is item-centric, i.e. to control the flow of individual jobs, most existing MFC mechanisms are resource-centric, i.e. focus on managing the capacity resources. While this was justified by technical constraints on real-time information feedback, advances in technology allow for new designs. In particular, smart products are cognizant of their local context and can communicate with one another through the Internet of Things, thereby enabling self-organized control of individual jobs. Despite this potential most application of smart products and the Internet of Things, including multi-agent systems for scheduling and holonic control, continue to focus on hierarchical, centralized data and control structures. In response, this study develops a simple item-centric MFC mechanism and uses simulation to proof the feasibility of self-organized control.

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.

Multi-stage assembly systems where the demand for components depends on the market-driven demand for end products, are commonly encountered in practice. Production Planning and Control (PPC) systems for this production context include Kanban, Materials Requirement Planning (MRP), Optimised Production Technology (OPT), and Demand Driven MRP (DDMRP). All four of these PPC systems are widely applied in practice and literature abounds on each of these systems. Yet, studies comparing these systems are scarce and remain largely inconclusive. In response, this study uses simulation to assess the performance of all four PPC systems under different levels of bottleneck severity and due date tightness. Results show that MRP performs the worst, which can be explained by the enforcement of production start dates. Meanwhile, Kanban and DDMRP perform the best if there is no bottleneck. If there is a bottleneck then DDMRP and OPT perform the best, with DDMRP realising lower inventory levels. If there is a severe bottleneck, then the performance results for DDMRP and OPT converge. This identification of contingency factors not only resolves some of the inconsistencies in the literature but also has important implications for the applicability of these four PPC systems in practice.

Production control systems (PCSs) control the flow of jobs in a production system. The selection of a suitable PCS in the context of make-to-order (MTO) is challenging, due to the characteristics of MTO businesses and the number of parameters or factors that comprise a PCS. The literature that compares PCSs in the MTO context reported contradictory results. In fact, there is a gap in the literature concerning which factors or parameters explain a PCS performance. This paper presents an analysis of comparative studies on PCS in the MTO context, using a systematic literature review, to reveal which control factors and manufacturing conditions influence a PCS performance. The analysis concentrates on studies that use simulation to assess the performance of PCSs. Our results indicate that the main difference in PCSs performance is the design of the control loops. Other important factors that must be considered in the choice of a PCS are the order release mechanism, the workload aggregation approach, and the workload estimation method used on control loops. A framework for choosing a suitable PCS for MTO companies is presented, considering these factors.

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.

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.

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.

PurposeThe purpose of this paper is to explore the adoption of lean practices by manufacturing companies in regions of low economic and technological development and to compare findings with previous studies from more developed regions highlighting important contextual differences. The paper uses the contingency theory to explore how contextual variables and scarce resources influence the adoption of lean practices.Design/methodology/approachA survey of 233 manufacturing firms was conducted in the State of Pará in the Amazon Region of Brazil.FindingsThe results demonstrate that six internal lean practices (single minute exchange of dies, human resource management, continuous flow, total productive maintenance, pull and statistical process control) and two external lean practices (supplier feedback and customer involvement) are implemented. However, the two external lean practices of just-in-time delivery by suppliers and supplier development were not implemented. Furthermore, from the 36 operating items comprised in eight lean practices that are being used, 13 were not implemented. As such, compared to developed regions, there is evidence for a more fragmented implementation in less developed regions. The results reveal empirical evidence explained by the contingency perspective, such as national, geographical, strategic context and culture.Originality/valueThere is broad evidence on lean implementation in developed and developing countries in the literature. However, little is known about lean implementation in poorer regions of developing counties. This is one of the first studies mapping lean implementation in a region with low economic and technological development. This has important implications for research and practice, especially to cross-country/cultural research on operation management.

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.

Lot splitting is an important strategy for avoiding the starvation of workstations, for accelerating the progress of jobs, and ultimately for improving overall due date performance. While lot splitting has received much attention in the extant literature, the use of alternative lot transfer policies that determine how the flow of lots through the production system is synchronised has been largely neglected. This study uses simulation to assess the performance of different lot synchronisation policies at release and different lot transfer policies on the shop floor in a ConWIP (Constant Work-In-Process) controlled job shop. The results suggest that different approaches should be applied at the release and shop floor levels. While lots should be synchronised in some form at order release, their progress on the shop floor should not be synchronised. Instead, lot coordination should be executed by dispatching in accordance with repetitive lots logic. The results further highlight that if lot progress is synchronised in systems that limit the workload, then lot release should also be synchronised. Otherwise, blocking may occur if lot progress on the shop floor depends on the release of lots, which in turn depends on lot progress. These findings have important implications for research and practice.

Although there is a broad literature on capacity management, there has been only limited attention on how to support short-term capacity control decisions, especially in high-variety make-to-order shops. While finite loading has been identified as a potential means of guiding capacity adjustments, the actual performance impact of this solution has not been adequately assessed. Using a simulation model of a make-to-order job shop, we compare the performance impact of four different forward and backward finite loading methods and a load trigger method recently presented in the literature. Results confirm the potential of finite loading to improve performance when compared to a general capacity increase. Yet all four methods are outperformed by the load trigger method. The capacity adjustments made under finite loading methods are determined by individual jobs and their properties. This may lead to no adjustments despite an overload period (e.g. if a job has a long due date but only one overload station in its routing) or to unnecessary adjustments when there is no overload (e.g. if a large job has a tight due date). This finding draws into question the use of finite loading altogether and reinforces the importance of the load trigger method.

The simplicity of Constant Work-In-Process (ConWIP) makes it one of the most widely adopted card-based production control solutions. Its simplicity, however, also limits the opportunities that are available to improve the concept. There are arguably only two major search directions: (i) to alter the meaning of cards away from controlling jobs; and (ii) to adopt alternative, more sophisticated backlog sequencing rules. In this study, we outline a simple, practical load-based ConWIP system that changes the meaning of cards. Rather than controlling the number of jobs, cards are associated with a certain amount of workload. Simulation results demonstrate the positive performance impact of limiting the total shop load. The Workload Control literature advocates the use of a corrected load measure as it better represents the direct load queuing at a station; but this worsens performance when compared to a shop load measure in the context of ConWIP.

A product lifecycle can be understood as a chain of events experienced by a product. These events do not only include the actual production but also service offerings which accompany the product throughout its life. This leads to integrated product and service offerings and Industrial Product Service Systems (IPS2). Major challenges in this context are product tracking and tracing, the triggering of service and the delivery of service. A new technology that holds much promise in addressing these challenges is blockchain. In response, this study first introduces blockchain technology before it discusses major opportunities in the context of IPS2. For example, blockchain inherently creates a synchronized database of all transaction at each node while smart contracts allow for responsive action. However, there are also challenges. For example, large amounts of redundant data, irreversible contracts and, consequently, reduced competition. While blockchain holds much promise, more needs to be done to unlock its full potential in the context of IPS2.

This paper proposes Jidoka (automation with a human touch) as the main guiding principle for SMEs digital transformation; understood as the continuous increase of levels of automation and intelligence at their shopfloors in an economic, social and technological sustainable way. It stresses the forgotten dual nature of Jidoka as an ‘automation approach’ as well as a ‘learning system’, capable of simultaneously improving the efficiency of manufacturing processes and cultivating the workforce skills needed to develop and/or adopt advanced automation solutions. The paper aims to remind the developers of automatic control systems in the Industry 4.0 era that it is only through human-machine mutual learning, characterized by cyber-physical-social interactions (cf. Jidoka 4.0 Systems), that sustainable higher levels of automation and intelligence can be achieved. Human operators need to know the processes that are being automated, so that, at the same time, this knowledge can be continuously updated and processes improved as digital technologies evolve: “Incorporating human learning, gives automation its human touch”.

Digital Twin is a term that was given to the concept of a virtual, digital equivalent of a physical product. However, most research to-date focusses on the monitoring of production equipment or large assets. This neglects the important role of services and Industrial Product Service Systems (IPS2) in value creation throughout a product life cycle. In response, this study used a systematic literature review to assess the current state-of-the-art of the literature on Digital Twin in the context of product service systems. An original sample of 59 papers was carefully analyzed, but only 2 studies appeared to focus on product service systems. Most of the remaining literature focusses on the use of Digital Twin for some forms of maintenance service. This study therefore calls for more research on the use of Digital Twin technology in the context of IPS2 and outlines possible applications for the stages in a closed loop product life cycle.

POLCA (Paired-cell Overlapping Loops of Cards with Authorization) is a production control system specifically designed for low-volume, high-mix and custom-engineered products. It is a visual control system that manages the flow of jobs though the shop floor by making use of overlapping loops of cards between pairs of successive manufacturing cells. These overlapping loops of cards realize a decentralized decision-making structure for job release. This means that jobs do not await release in a centralized pre-shop pool. Rather jobs are immediately forwarded to a gateway manufacturing cells at their shop arrival, where they wait in release lists for available POLCA cards. However, the Workload Control literature has shown that using a centralized pre-shop pool provides important benefits. Therefore, this paper investigates the impact of centralized job release on POLCA performance. Using simulation, we demonstrate that centralized job release outperforms decentralised release if the right card acquisition rule for job release is used. This has important implications for both research and practice calling for more research on POLCA systems.

China’s Belt and Road Initiative (BRI) is one of the world’s largest infrastructure projects, with its potential political and economic impact being widely discussed since its inception in 2013. Yet the phenomenon has received only limited attention in the Supply Chain Management (SCM) literature. In response, we first conduct a broad systematic review of the literature to assess how China’s BRI is portrayed. Using this as a backdrop, we then distil the likely impact of the BRI on location decisions and supply chain flows. Finally, in a broader discussion of the SCM literature, we explore the implications of the BRI for future research in four key areas: supply chain configuration, supply chain resilience, sustainable SCM, and cross border SCM. While these areas are not new, the BRI presents a unique context that can be used to enhance theory and understanding in each area. The BRI reduces time distance independent of geographical distance by diverting supply chain flows from established routes to new routes via far less accessible regions. This introduces new risks and sustainability issues that call for multi-criteria decision support systems. Another important issue is the adoption and diffusion of the BRI since this will ultimately determine project success.reduces time distance independent of geographical distance by diverting supply chain flows from established routes to new routes via far less accessible regions. This introduces new risks and sustainability issues that call for multi-criteria decision support systems. Another important issue is the adoption and diffusion of the BRI since this will ultimately determine project success.

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: labor and machines. This study therefore uses simulation to investigate the performance of WLC in Dual Resource Constrained (DRC) highvariety shops with fully interchangeable labor. By considering several environmental factors and different labor 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 labor availability at release, as proposed in previous research, could not however be confirmed. Thus, the original release method can be applied if labor is fully interchangeable. In terms of labor 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 labor absenteeism than lowering the input frequency of work

Lot splitting is an important approach for shops that compete on short delivery times. Similarly, such shops can benefit from load-limiting order release mechanisms that balance workloads and regulate throughput times. Yet few studies have examined the combined effect of lot splitting and load-limiting order release. We use simulation to assess the combined effect of lot splitting and P aired-cell O verlapping L oops of C ards with A uthorization (POLCA), an important load-limiting order release mechanism in the context of time-based competition. The experimental design includes different lot sizes, lot transfer policies, and POLCA quanta, i.e. the limit on the size of jobs represented by a single POLCA card. Lot splitting improves performance if lots can proceed independently as this ensures the quick replenishment of queues at downstream stations. However, we find that enforcing the synchronization of all lots that make up a job at every routing step leads to a deterioration in performance. This extends previous research, which appears to have overemphasized the positive effects of lot splitting. Meanwhile, although POLCA cards were originally used to represent lots, we demonstrate that using cards to represent a certain amount of workload can improve percentage tardy performance. This may also have resonance with other card-based solutions, including kanban.

Industrial cluster is becoming an ever more important cost-effective industry development mode especially when enterprises are required to give more rapid responses to the frequently changed customized demands. The explosive number of homogeneous enterprises/suppliers with geographic proximity provides multiple options for each supply chain stage, which thus leads to higher potential to form a more satisfactorily performed assembly supply chain (assembly system) in industrial clusters. However, the increased candidate options also incur inevitably higher decision complexity to the decision model of configuring such cluster supply chains. The situation may be more challenging if the autonomous decision requirement of individual suppliers is accommodated. A general assembly cluster supply chain configuration (ACSCC) model is established which considers both horizontally and vertically collaborations in a cluster, meaning it accommodates the typical cluster relationships including subcontracting and outsourcing. In order to achieve the complexity reduction and autonomy protection, a newly emerged decomposition-based solution method named augmented Lagrangian coordination (ALC) will be adopted. Especially, two classical ALC formulation variants named the centralized coordination formulation and the distributed coordination formulation are innovatively integrated to form a hybrid ALC solution strategy, which deals with different assembly branches with different alliancing structures. Experimental results have proved the effectiveness of the proposed hybrid ALC method for the ACSCC problem. From the perspective of supply chain management, a set of sensitivity analysis for profit of each collaborative enterprise is conducted to obtain some important managerial insights.

The reluctance or incapability of further increasing production resources has made many enterprises suffering from high resource-workload situation. Production dynamics thus cannot be resolved by single resource independently, yet have to make an integral use of the adjustable capability of multiple resources of the whole system in a synchronized way. This paper considers a dynamic production logistics (PL) process comprising multiple independently operated PL stages, which adopts Internet of Things to capture real-time execution dynamics and rely on plan (re)scheduling and cloud-based resources re-configuration to cope with dynamics. A generic dynamic production logistics synchronization (PLS) solution is proposed. Qualitatively, a multi-phase multi-stage multi-degree synchronization control mechanism is put forward toward a PL system with generic structure and typical execution dynamics. Quantitatively, collaborative optimization is applied to assist the PLS to obtain the synchronization results. With a real-life case study, the effectiveness of the proposed mechanism and method has been verified. A set of sensitivity analysis is also conducted toward dynamics of different degree and different time, which provides significant managerial implication to PL managers to better deal with dynamics.

Paper aims POLCA is a production control system that forwards to gateway manufacturing cells jobs that arrive to a manufacturing system. However, Workload Control literature shows benefits from using a centralized release pre-shop pool. Thus, the paper aims at investigating the performance impact of incorporating centralized job release into POLCA, in high-variety make-to-order production. Originality This has not been investigated before. Research method Simulation was used for experimentation. Main findings In the case of the general flow shop, a manufacturing system configuration aligned with many real-world production systems, the investigation shows that adding centralized job release to the POLCA system, together with job release based on job workload, leads to a markedly improvement of job delivery performance. Implications for theory and practice The results show theoretical and practical relevance of applying central job release to POLCA system, in high-variety production, due to its markedly positive impact on delivery performance.

Gemba Walks are an important mean of vertical integration in Lean Manufacturing environments. They ensure that all levels of the company stay connected with the front-line, “the Gemba”, where the actual value is created. However, traditionally Gemba Walks have been restricted to one location. This is a shortcoming in production environments characterized by interconnected and often globally dispersed problems where information from several locations is needed simultaneously. In response, this paper explores the emergence of new forms of Gemba Walks enabled by the adoption of new digital technologies. We intend to identify the advantages and disadvantages of using digital technology to support the execution of these new forms of Gemba Walks in more complex, globalized environments and to get a grasp of the extent to which digitalization changes communication characteristics between the parties involved.

30th International Conference on Flexible Automation and Intelligent Manufacturing (FAIM2021) 15-18 June 2021, Athens, Greece., POLCA (Paired-cell Overlapping Loops of Cards with Authorization) is a decision support system for material flow control under Quick Response Manufacturing. It operates in the context of low-volume, high-mix, and cellular manufacturing. While there is an increasing literature on POLCA performance, current studies usually assume full availability of components (or parts) at assembly stations, neglecting parts manufacturing and feeding. Therefore, this study uses simulation to assess POLCA performance in a two-stage production system, where at the first stage parts are manufactured and at the second, they are assembled into end-products. The study demonstrates that using POLCA to control both production stages, manufacturing and assembly, significantly outperforms the use of POLCA at the assembly stage only, leading to important reductions of the total throughput time of orders and on the percentage of tardy orders. Statistical analysis of our results was conducted using ANOVA., This work has been supported by FCT – Fundação para a Ciência e Tecnologia within the R&D Units Project Scope: UIDB/00319/2020

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Most shops in practice are constrained by more than one resource. Consequently, a large body of literature on dual resource constrained shops has emerged. This research typically focuses on worker assignment rules, with attention being on when and where to move workers. In contrast, the decision concerning who to reallocate to a station has received limited attention. The limited prior work assumes workers are assigned to a new station as soon as they become available or seeks to minimise the risk of worker idleness. Using simulation, we question this assumption and show that it can be beneficial to introduce additional worker idleness to ensure workers only work at their most efficient station(s). In general, it is less likely that there are several workers available for one station than it is for there to be multiple stations available for one worker. Consequently, the Who Rule is used less frequently than the Where rule and has less of an impact on performance. Finally, considering the criticality of work orders as part of the Where Rule is important in assembly shops; but if labour is heterogeneous then the focus should be on efficiency. The findings have important implications for research and practice.

Literature on two-stage assembly systems typically assume that parts (subassemblies) require several sequential operations at the first production stage. However, parts can often be produced at a single station. This shifts the focus away from coordination to the provision of parts. The literature on parts feeding typically assumes the full availability of parts at stock points (e.g. warehouses or supermarkets), thereby neglecting the potential impact of capacity constraints at upstream stations. In response, this study assesses the performance of different parts feeding policies (kitting and line stocking). Simulation results show limited operational performance differences between kitting and line stocking in to-stock systems, with the main difference being where stock points are located. However, results also highlight the potential for producing subassemblies to-order if the constraint is how much (and not where) stock can be kept. This links together the literature on parts feeding with that on customer order decoupling points.

This paper proposes a reconfigurability index. Its development is based on five core characteristics, namely modularity, integrability, diagnosability, adaptability and customization. The index takes into consideration the interdependencies that may exist among them. The analytic network process (ANP) method is used to attribute importance weights to each core characteristic. This index can be very useful in practice since it can guide manufacturing companies to a better understanding of the various enablers of reconfigurability, as well as in the decision-making process, to decide which core characteristic requires more attention, in order to further improve the reconfigurability in existing manufacturing systems.

Most job shops in practice are constrained by both machine and labor availability. Worker assignment in these so-called Dual Resource Constrained (DRC) job shops is typically solved in the literature via the use of meta-heuristics, i.e. “when” and “where” rules, or heuristic assignment rules. While the former does not necessarily lead to optimal results, the latter suffers from high computational time and complexity, especially when there is a large number of workstations. This paper uses game theory to propose a new worker assignment rule for DRC job shops. The Gale-Shapley model (also known as the stable marriage problem) forms a ‘couple’ made up of a worker and machine following a periodic review strategy. Simulation is used to evaluate and compare the proposed model to “when” and “where” rules previously proposed in the literature. Simulation experiments under different conditions demonstrate that the Gale-Shapley model provides better results for worker assignments in complex DRC systems, particularly when the workers have different efficiency levels. The implications of the findings for research and practice are outlined.

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.

Increasing consumer awareness and soaring prices for raw material make reverse logistics an ever more important aspect of the product life cycle. However, most research focuses on the remanufacturing and recycling process leaving the actual tasks of waste collection behind. Moreover, existing research on waste collection typically assumes the problem to be deterministic, neglecting its stochastic nature. This study first diagnoses the solid waste collection problem; it is classified as an inventory control problem with confluent material flows and stochastic demand. A type of control system designed for this kind of problem is the kanban system. In response, the applicability of a kanban system for solid waste collection is discussed. While kanbans are a suitable mean to signal time and quantity of waste collection, the large quantity of collection points and geographical distances involved hinder its direct application. How the kanban system can be driven by the Internet of Things (IoT) was consequently the second objective of this study. Using a framework of an IoT driven production logistics system the control structure of the original kanban system has been analyzed. Out of this analysis the architecture of an IoT driven kanban system for solid waste collection is proposed.

Waste reduction is one of the main principles of lean, but it has been taken for granted that we have a common understanding of what waste means. We first present a critical, qualitative discussion that identifies four distinct waste concepts. We then conduct a systematic review of the literature that examines the different uses of these concepts. We find that only the classic concept of the seven wastes and the concept of waste as non-value-adding activity are widely applied. However, both concepts are, at times, not only incompatible but used in a way that leads to open contradiction. A new definition, centred on an efficient, timely transformation process seeks to consolidate the literature. We outline two distinct waste types: (i) obvious waste, to refer to any waste that can be reduced without creating another form of waste; and, (ii) buffer waste, to refer to any waste that cannot be reduced without creating another waste. The paper has important implications for practice. To reduce waste, managers must undertake three interlinked tasks: the elimination of obvious waste; the reduction of variability to transform buffers into obvious waste; and, the balancing of remaining buffers to best achieve performance targets. The paper supports managers in their endeavours to identify waste, which is an important precursor to waste reduction/elimination.

Kanban systems are simple, effective means of improving production that are widely applied in practice. Based on the logistic process involved, kanban systems can be divided into constant order-quantity and constant order-cycle systems. The former has received much research attention, but the latter, also known as a milk run, has been relatively neglected. Further, most prior work has been based on deterministic data, which is an assumption often violated in practice. We present the case of a manufacturer of domestic water heating equipment where a constant order-cycle kanban implementation initially failed. A structured Define–Measure–Analyse–Improve–Control approach is adopted to improve the process. It was revealed that the failure was due to high variability in the logistic processes involved. Decreasing this variability resulted in a reduction of tardy replenishment routes from 50 to 3%; a reduction in the route time coefficient of variation from 40 to 16%; and a reduction in the mean route t...

A production logistics system is often subject to high operational dynamics due to large working areas, frequent resource interactions, long operation periods and intensive human involvement. Researchers have applied system dynamics to design the structure of statistically robust systems which accommodate common dynamics. Yet this approach begins to lose its feasibility because dynamics anticipation and statistics are becoming more difficult in ever more competitive markets and adjustments to system structure typically incur high costs. In response, this study explores how a robust information structure can be designed and real-time control schemes for controlling the dynamics inherent to real-life systems applied. Motivated by the wide application of industrial Internet-of-Things (IoT) systems, this paper investigates the typical production logistic execution processes and adopts system dynamics to design cost-effective IoT solutions. The internal and external production logistic processes are first inve...

Part 1: Lean Production; International audience; In this paper, the authors present practical insights in order to propose a Quality Management Framework for Digital Lean Manufacturing. The rationale behind this proposed framework is that the individual ISO 9000:2015 Quality Management pillars are rather different when it comes to their objectives and their tasks at hand when using Human capabilities and/or Digital technologies capabilities in a strategic way for (i) Quality Planning, (ii) Quality Control, (iii) Quality Assurance, and (iv) Quality Improvement in the context of the emerging paradigm of Digital Lean Manufacturing Systems.

The emergence and subsequent popularization of lean has been one of the most significant developments in the history of operations management. However, there is a lack of systematic theory on the control framework underlying lean production. It is therefore difficult to conduct more in-depth research on Lean theory, specifically in the context of emerging technologies as smart manufacturing or Industry 4.0. In this study, process control theory is used to re-define several major lean methods and tools. Then a Lean-Oriented Optimum-State Control Theory (L-OSCT) is proposed that integrates these lean methods and tools into optimum-state control theory. On the level of method and mechanism, we adopt a recently emerged synchronization approach to obtain global-wide leanness of a large-scale system. L-OSCT provides dynamic process control in industrial networking systems. At last, a case study in a large-size paint making company in China is used to validate the effectiveness of the approach. Funding Agencies|National Natural Science Foundation of China [51475095, 51875251]; Natural Science Foundation of Guangdong Province [2016A030311041, 2017A030313401]; National Ministry of Education "Blue Fire Plan" (Huizhou) Industry-Academia-Research Joint Innovation Fund (2018-2021); Fundamental Research Funds for the Central Universities [11618401]; 2015 Guangdong Special Support Scheme [2014TQ01X706]

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.

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 f...

The majority of manufacturing systems in practice are constrained by machine capacity and labour capacity. Consequently a broad literature on Dual Resource Constrained (DRC) shops exists. However, to best of our knowledge, no systematic review of the literature has been presented. Rather, existing reviews follow an ad-hoc procedure for article selection. In response, this study presents a systematic review of the literature concerned with DRC operating issues, such as worker assignment and production planning and control methods. Results highlight that, while early literature on dual resource constraint job shops was mainly simulation based, recent literature tends towards advanced scheduling mechanisms. This arguably introduces a bias towards deterministic contexts. Moreover, most DRC literature focuses on shop floor control decisions as labour assignment and dispatching. This neglects higher-level planning and control methods, such as order release control.

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.

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. The approach has received significant research attention but has remained largely unchanged since its introduction in the late 1990s. The main improvements have occurred in the context of an electronic POLCA system, but such developments undermine the simplicity of the original card-based concept. We ask: is there any refinement possible to enhance the performance of POLCA without jeopardizing its simplicity? By analyzing POLCA, two possible refinements are identified: (i) the choice of rule to support both the card allocation and dispatching decisions; and (ii) the use of a starvation avoidance mechanism to overcome premature station idleness, as reported in the context of load limiting order release. Using simulation, we demonstrate that performance gains can be obtained by using different rules for card allocation and dispatching other than the earliest release date rule typically applied in POLCA for both decisions. Further, results demonstrate performance improvements for all combinations of card allocation and dispatching rules considered via the addition of a simple starvation avoidance mechanism. Both refinements significantly enhance POLCA performance, potentially furthering its application in practice. info:eu-repo/semantics/publishedVersion

“This is a post-peer-review, pre-copyedit version of an article published in Advances in Intelligent Systems and Computing. The final authenticated version is available online at: https://doi.org/10.1007/978-3-319-56538-5_40" POLCA (i.e. Paired-cell Overlapping Loops of Cards with Authorization) is a card-based decision support system for production control developed to support the adoption of Quick Response Manufacturing. In POLCA, the flow of jobs through the production system is controlled through a combination of release authorisations and production control cards - POLCA cards. In this paper, we discuss a load-based version of the POLCA system (LB-POLCA), which draws on recent insights from the Workload Control literature. In this context, a question arises: what is the load (e.g. in hours) that a POLCA card should represent? Using simulation, we demonstrate that insights from the Workload Control literature cannot be straight transferred to the POLCA system. Results further demonstrate that significant performance improvements for all card acquisition rules considered in this study can be realized when the POLCA card represents the operation time the job imposes to the second station of the pair. info:eu-repo/semantics/publishedVersion

Workload Control is a production planning and control concept developed for high-variety job shops. It integrates two control mechanisms: (i) input control, to regulate the inflow of work to the system; and (ii) output control, which uses capacity adjustments to regulate the outflow of work from the system. Much Workload Control research has focused on input control, while output control has been largely neglected. Only recently has research emerged that uses Workload Control theory to guide capacity adjustments. Yet this literature focuses on capacity adjustments (output control) only – it fails to integrate it with Workload Control’s input control element. In response, this study explores the performance impact of Workload Control when input control (controlled order release) and output control (capacity adjustments) are combined. Job shop simulation results demonstrate that input and output control can and should play complementary roles. Both elements significantly enhance performance in isolation, and performance effects appear to complement each other. Further, results indicate that the choice of the workload threshold that triggers capacity adjustments has a stronger impact on performance than the actual size of the adjustment. The measure of workload used to guide the load-based order release decision is also used to determine the workload threshold that triggers the capacity adjustment. This facilitates implementation in practice. Finally, although our study is on Workload Control, the findings have important implications for other production planning and control concepts.

Order release is a key component of Workload Control - a production planning and control system that aims at balancing workloads across workstations, while ensuring the timely release of jobs (or orders) to the shop floor in order to meet due dates. Several release methods have been proposed and evaluated in the WLC literature. A major criterion to distinguish between release methods is whether they take the release decision at periodic time intervals or continuously. This paper aims at improving WLC order release by incorporating a starvation avoidance trigger into continuous release. Using simulation, we demonstrate that significant performance improvements in terms of mean tardiness and standard deviation of lateness can be obtained. These results are expected to have important implications for industrial practice and for future research on WLC. info:eu-repo/semantics/publishedVersion

International audience; 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 prioritizing 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, prioritization, given to rush orders, leads to the best overall shop performance.

Workload control (WLC) is a leading production planning and control (PPC) solution for small to medium sized enterprises (SMEs) and make-to-order (MTO) companies, but when WLC is implemented, practitioners find it difficult to determine suitable workload norms to obtain optimum performance. Theory has provided some solutions (e.g., based on linear programming) but, to remain optimal, these require the regular feedback of detailed information from the shop floor about the status of work-in-process (WIP), and are therefore often impractical. This paper seeks to predict workload norms without such feedback requirements, analysing the influence of shop floor characteristics on the workload norm. The shop parameters considered are flow characteristics (from an undirected pure job shop to a directed general flow shop), and the number of possible work centres in the routing of a job (i.e., the routing length). Using simulation and optimisation software, the workload norm resulting in optimum performance is determined for each work centre for two aggregate load-oriented WLC approaches: the classical and corrected load methods. Results suggest that the performance of the classical approach is heavily affected by shop floor characteristics but no direct relationship between the characteristics and norm to apply could be established. In contrast, results suggest that the performance of the corrected load approach is not influenced by shop floor characteristics and the workload norm which results in optimum performance is the same for all experiments. Given the changing nature of MTO production and the difficulties encountered with the classical approach, the corrected load approach is considered a better and more robust option for implementation in practice. Future simulations should investigate the influence of differing capacities across work centres on the workload norm while action research should be conducted to apply the findings in practice.

International audience; The importance of digitalization is widely recognized, but digital transformation is not commonplace, and companies often struggle to face the challenges it entails. Digitalization and digital transformation are even more challenging for manufacturing SMEs. In this paper, we aim at investigating the barriers to digital servitization faced by manufacturing SMEs. We build on a literature review on barriers and obstacles to digital servitization, and present a set of case studies that enable us to identify the main barriers these French manufacturing SMEs face in their move toward digital servitization. Our findings show that digital servitization is at a very early stage in these SMEs, and that the main barriers they face are both organizational and customer-related.