Cross-training workers in Dual Resource Constrained systems with heterogeneous processing times

In this paper, we explore the effect of cross-training workers in Dual Resource Constrained (DRC) systems with machines having different mean processing times. By means of queuing and simulation analysis, we show that the detrimental effects of pooling (cross-training) previously found in single resource constrained (SRC) heterogeneous systems are also apparent in DRC heterogeneous systems. Fully cross-training workers in DRC heterogeneous systems is only beneficial if the differences between mean processing times are not too large, otherwise cross-training should be pursued within homogeneous subgroups of machines. Due to the limited machine availability, DRC systems are unable to use some of the potential assignment flexibility from cross-trained workers (pooled queues) that can be used in SRC systems. However, it appears that this restriction in the DRC system may even improve the system mean flow (waiting) time performance compared to the SRC system for relatively large differences in processing time. Finally, in fully flexible multiple server queuing systems, restricting the assignment flexibility by applying a decentral when-rule (i.e. a commonly used labour assignment rule in practice and research) instead of a central when-rule also seems to improve the mean flow time performance under processing time differences.     

On the who-rule in Dual Resource Constrained (DRC) manufacturing systems

The who-rule is a labour allocation rule used in labour and machine-limited dual resource constrained (DRC) systems. A who-rule selects one worker out of several workers to be transferred to a work centre. By means of a practical instance, the paper shows that the who-rule plays a role in the daily practice of worker assignment. Previous simulation studies, however, either have not mentioned the who-rule or have treated it as a fixed factor. The present study will explore the need of including the who-rule in simulation studies. It will describe in detail at what decision moments the who-rule needs to be applied in simulation. Further, it will explore the flow time effects of applying different who-rules in several DRC systems where labour flexibility is limited and workers differ with respect to task proficiencies, the number of skills they possess and the loads of work centres for which they are responsible. As with other labour allocation rules, the impact of the who-rule depends on the specific DRC shop modelled. The paper will show that the average labour utilization, and the types and extent of worker differences, determine the impact of the who-rule on shop performance.     

Multi-level heterogeneous worker flexibility in a Dual Resource Constrained (DRC) job-shop

The majority of research on labour flexibility in a DRC job-shop has focused on the situation where all workers are equally trained. In practice, it is likely that workers would not be trained equally and would possess different skills. In this paper, the situation where workers receive different levels of training across the various departments as well as possessing different levels of proficiency at each task is studied. Research results suggest that, even at the same level of shop flexibility, the mixture of cross training can have a significant impact on shop performance. Indeed, results suggest that it is better to have a mix of workers with no flexibility and some workers with very high flexibility rather than all workers with equal flexibility.     

Reliability assessment for a stochastic manufacturing system with reworking actions

This article evaluates the system reliability of a manufacturing system with reworking actions, where the system reliability is an essential indicator to determine whether the manufacturing system is capable or not. Based on the path concept, we transformed the manufacturing system into a stochastic-flow network in which the capacity of each machine is stochastic (i.e., multistate) due to failure, partial failure, and maintenance. In such a manufacturing network, the input flow (raw materials/WIP; work-in-process) processed by each machine might be defective and thus the output flow (WIP/products) would be less than the input amount. To analyze the different sources processed by the manufacturing network, we decomposed the network into one general processing path and several reworking paths by a graphical technique. Subsequently, an algorithm for the manufacturing network was proposed to generate the lower boundary vector which allows sufficient products to satisfy the demand. In terms of such a vector, the system reliability can be derived easily.     

Performance evaluation of cellular layouts: Extension to DRC system contexts

This study involves a comparison of the performance of functional layouts (FL) and cellular manufacturing (CM) systems in a dual-resource-constrained (DRC) system context. Past studies of FL and CM have been based mostly on single-resource-constrained (SRC) systems. Recent studies have included labour-related factors, but have assumed high labour flexibility levels, and shown the superiority of CM. In this study we assume more realistic levels of labour flexibility, and factors such as lot size, set-up reduction, labour assignment and transfer rule, and scheduling rules. The parameter range in which CM can outperform efficiently operated FL, in a DRC context, are indicated.     

Performance comparison of virtual cellular manufacturing with functional and cellular layouts in DRC settings

This study investigates the performance of virtual cellular manufacturing (VCM) systems, comparing them with functional layouts (FL) and traditional, physical cellular layout (CL), in a dual-resource-constrained (DRC) system context. VCM systems employ logical cells, retaining the process layouts of job shops. Part family-based scheduling rules are applied to exploit the benefits of group technology while retaining the flexibility and functional synergies of the job shop. Past studies of VCM have been based entirely on single-resource-constrained (SRC) systems, i.e. as purely machine-limited systems, assuming that resources such as labour and tooling do not restrict the output. However, given the fact that labour forms a second major constraining resource, and many of the advantages associated with cellular manufacturing are derived from labour flexibility, it becomes necessary to extend the research to DRC systems. In this study, we assume several levels of labour flexibility in all three systems, in addition to other relevant factors such as lot size, set-up reduction, and labour assignment rules. It is shown that VCM can outperform efficiently operated FL and CL in certain parameter ranges, as preliminary research has shown so far. However, it is shown that CL tends to outperform both VCM and FL in the parameter ranges customarily advocated for CL, namely, low lot sizes, adequate levels of set-up reduction, cross training of workers, and worker mobility within cells.     

Labour flexibility and assignment policies in a job shop having incommensurable objectives

This study evaluates operating policies for offering a near-perfect delivery performance for vital customers in dual resource-constrained (DRC) job shop environments. Prior studies have considered this problem in machine-limited settings, and shown that dispatching rules that help realise a near-perfect delivery performance for vital customers necessarily deteriorate delivery performance for other customers served by the shop. This study extends prior work, and considers additional tools that can be used by managers in DRC shops such as labour flexibility, and assignment rules that incorporate customer-based information to deploy workers to departments containing high-priority jobs. Results show that labour flexibility in conjunction with appropriate decision rules allows for enhanced delivery performance for both vital and normal priority customers. These results hold even under conditions where 80% of the shop's workload is compromised of high-priority orders.     

Managing worker flexibility and attrition in dual resource constrained job shops

Worker flexibility is an attractive option for enhancing manufacturing performance, since it provides several strategic advantages, and also allows the firm to buffer against uncertainty. In this paper, we investigate issues related to acquiring a flexible work-force in those dual resource constrained (DRC) job-shops that have high learning costs and the presence of worker attrition. Our results show that significant improvement in traditional shop related measures can be attained at even very high attrition rates by incrementally training each worker in one additional department. However, this improvement comes at the expense of productivity losses which shop managers may not be willing to accept. The nature of the tradeoffs that exist in acquiring this incremental worker flexibility are addressed. Two strategies for improving shop performance, based on incrementally training workers or reducing attrition rates, are also recommended for the DRC shop modelled in our study. Conditions under which either of these two strategies should be pursued by the shop managers are also identified.     

Determining the number of kanbans: a step toward non-stock-production

Just-in-time (JIT) production is a philosophy that calls for reducing work-in-process (WIP) inventory to aid process improvement and reduce process variability. In some cases, JIT production has been misinterpreted as a method that would lead to zero or minimal WIP with a lot size of one. There are no models or theories to achieve the JIT goal, i.e. non-stock-production (NSP), and, in particular, to help determine when and where to maintain this minimal inventory. A kanban system acts as the nerve of a JIT production system whose functions are to direct materials just-in-time to workstations in stages of manufacturing, and to pass information as to what and how much to produce. Indeed, the number of kanbans between two adjacent workstations decides the inventory level of that pair of workstations. With the objective of minimizing WIP inventory level, one model dealing with three cases of production configuration is developed for deciding the optimum number of kanbans. The model is then solved using a Markov process approach which considers the demand of finished products as the departure rate and the production rates of stations as arrival rate. In this paper, the model and solution procedure are illustrated with a numerical example.     

Gated MaxWIP: A strategy for controlling multistage production systems

This study considers serial production systems with exponential processing times. The systems are balanced, i.e. all resources have the same production rate capacity. Preceding the system there is a 'gate' set to regulate the flow of material into the system. A control strategy directs each resource when to work or stay idle. The trade-off is between throughput (TP) and work-in-process (WIP). G-MaxWIP is a production control strategy allowing resources, except for the gate, to work unconstrained. The gate 'shuts' once the system's WIP reaches a maximum allowable level. We study the properties of G-MaxWIP and compare it to 'simple pull' and CONWIP. Our main findings are: G-MaxWIP is superior to simple pull. For any simple pull system operating a fixed set of resources it is possible to find G-MaxWIP systems that operate the same resources with less WIP while maintaining the same (or higher) TP. G-MaxWIP is superior to CONWIP. For any CONWIP system operating a fixed set of resources it is possible to find G-MaxWIP systems that operate the same resources with less WIP while maintaining the same (or higher) TP.     

JIT vs. WIP— a trade-off analysis

This paper develops a decision rule to enable an a priori classification of a production system that should utilize a JIT- or WIP-type inventory control policy. A two-station deterministic serial production system is analysed. A parameter a— the ratio between WIP and maximum shortage—is defined, and a cost function K — f( α) is modelled. It is shown that α?—an optimum value of α—is a characteristic parameter of the system, can be evaluated a priori based on known parameters, and can serve to identify a production system as JIT type or WIP type. The concept of an OC curve of a system is introduced and it is concluded that JIT is not always favourable over WIP.

An extension of the deterministic case shows that α? can be expressed, among others, in terms of MTBF and MTTR. The paper concludes with a numerical example.     

Impact of worker and shop flexibility on assembly cells

Flexibility can counter the negative effects of the loss of pooling synergy in cellular systems. In this study we define flexibility as the ability of assembly cells to reallocate resources to accommodate changes in family assignments (i.e. shop flexibility) and the ability of workers to move between cells (i.e. worker flexibility). We investigate the impact of shop and worker flexibility on different assembly cells faced with product mix variability over a wide range of experimental conditions. Three types of cellular shops are considered: strict cell shops (where each cell is dedicated to producing only one product family), flexible cell shops (where each cell can produce multiple product families), and hybrid cell shops (where some of the cells are strict and the rest are flexible). Results indicate that there is no cell shop that outperforms others, under all experimental environments. However, flexible cell shops showed significant advantages when the setup times were low, while hybrid cell shops provided an excellent alternative when setup times and the product mix unbalance were at ‘moderate to high’ levels. The strict cell shops demonstrated excellent performance when setup times were high, and the product mix unbalance was ‘minor’. Finally, the results suggest that in most cases, the implementation of only worker flexibility resulted in the majority of improvements with respect to the average percentage of jobs tardy.     

Push and pull strategies for controlling multistage production systems

This study considers push and pull strategies to control multistage production systems with random processing times. Such systems are important as they mirror the level of complexity often encountered in practice. We start with definitions of push and pull systems, and develop a framework to compare multistage production systems based upon work-in-process (WIP) and throughput (TP) tradeoff. Surprisingly, we find that often push out performs pull, i.e. push systems accumulate less WIP than pull systems, while maintaining higher PT Concerning pull systems we find that WIP linearly increases in the number of stages and that WIP is not affected by variation in processing time. Concerning push systems we find that the release of material into the system in deterministic time intervals greatly improves performance.     

Using the when/where rules in dual resource constrained systems for a hybrid push-pull control

This paper proposes a production control system, DRC-HPP, which uses the when/where rules in dual resource constrained (DRC) systems for a hybrid push-pull (HPP) control, to overcome some difficulties in modelling/implementing DRC/Kanban systems. These rules and the novel ‘process-or-transport’ and ‘whereto’ rules are embedded in some policies workers use to decide when to process (transport) parts, and where (whereto). Unlike most control systems, in which a group of workers is always responsible for transporting and another group is always responsible for processing parts, workers in DRC-HPP are responsible for both transporting and processing parts, as in the Toyota Sewn Products Management System (TSS). Yet, unlike TSS, DRC-HPP can be applied in any layout type. Workers transport parts when they are idle in part processing to enhance their utilisations and synchronise transportation. Since the transportation does not require special worker skills, the cost of training workers is not incurred. DRC-HPP is compared with different benchmarks through simulation experiments to evaluate its performance. It performs well under relatively short transportation times with respect to processing times. If they are relatively longer, the issue becomes to determine the number of workers to achieve a performance level. DRC-HPP also facilitates bottleneck management.     

Workload control in dual-resource constrained high-variety shops: an assessment by simulation

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.     

Performance Opportunity for Workforce Agility in Collaborative and Noncollaborative Work Systems

To gain insight into the potential logistical benefits of worker cross-training and agile workforce policies, we study simple models of flexible workers in serial production systems. The primary control issue is how to assign workers to jobs/stations over time. Under assumptions of complete worker flexibility and collaborative work, we prove that a simple expedite policy minimizes along each sample path the cycle time (delay) for each job. Therefore, the expedite policy also minimizes work in process and maximizes throughput along every sample path. We also compute the performance improvement opportunity achievable using flexible workers as opposed to the optimal static allocation of workers. This enables us to examine th e factors that make workforce agility a potentially attractive strategy. We also consider the intuitive analog of the expedite policy for the noncollaborative work environment, which we call the pick-and-run policy; however, we demonstrate by counterexample that it is not always optimal. Finally, we extend some of our insights from the demand-constrained environment to a capacity-constrained environment operating under a CONstant WIP (CONWIP) protocol     

Critical WIP loops: a mechanism for material flow control in flow lines

Critical WIP loops (CWIPL) is a proposed material flow control mechanism for a balanced flow line environment aiming at improving throughput and lead time. The mechanism establishes critical loops which their WIP identifies the time of releasing raw material to the line. So, through control of WIP level of critical loops the material flow is managed. The proposed mechanism releases the raw material to the line if the ‘total WIP of the line’ or ‘the WIP of the last machine’ is less than the limit. Besides the aforementioned condition, the necessary condition for releasing the raw material to the line is ‘idleness of the first machine’. Simulation is used to compare the performance of the CWIPL, CONWIP and G-MaxWIP. Different line characteristics such as number of machines, processing time distributions and the maximum WIP level of the line are considered in numerical examples. The results show that CWIPL improves both throughput and lead time compared with CONWIP, while CWIPL has better results than G-MaxWIP with respect to both throughput and lead time in the flow line that has less than nine machines.     

The moderating role of temporary work on the performance of lean manufacturing systems

Companies are extensively employing lean manufacturing practices and temporary work, which at face value are in stark contrast to each other. While lean manufacturing emphasises the value of workers, temporary work refers to precarious work arrangements that, based on social exchange theory, may harm workers’ commitment. The objective of this paper is to unveil the role of temporary work on the lean manufacturing – operational performance (i.e. cost, quality, delivery, flexibility) relationship. To answer our research question and test our hypotheses we utilise cross-country data collected through the sixth iteration of the International Manufacturing Strategy Survey and conduct multilevel regression analysis. Our results indicate that while lean manufacturing improves operational performance, the use of temporary work positively influences the relationship between lean manufacturing and mix and volume flexibility performance.     

On the steady state of the replicating portfolio: accounting for a growth rate

For the risk management and transfer pricing of non-maturity liabilities, banks in Europe often use a so-called replicating portfolio technique. A commonly used implementation is replication of a fixed investment rule every time period. This paper deals with the development of the portfolio in the long run, when using this methodology. Applying this replicating portfolio technique yields, after a while, a steady state. Besides the straightforward result when volume is constant, we solve the steady states for the case where the funds (volume) grow with a fixed rate (e.g. due to credited interest or growth in GDP). We therefore define a system growth process, alternative to the Markov process (when volume is constant). From a transfer pricing and risk-management point of view, the resulting portfolio should satisfy certain requirements concerning return and flexibility. Once the steady state can be calculated for given growth rates, the investment policy can be specified. The importance of taking account of a growth rate is illustrated. Growth in volume implies that a different rule will converge to the desired steady state. This is illustrated analytically and with numerical examples. The purpose of the paper is not to find the ideal hedge strategy for non-maturity liabilities, but to improve the existing risk management without any implementation costs for the banks. Given the currently used methodology, accounting for a growth rate can significantly improve the risk management of non-maturity liabilities. RID="*" ID="*" I thank Anja De Waegenaere, Peter Kort and an anonymous referee for useful comments on an earlier draft.     

CWIPL II,a mechanism for improving throughput and lead time in unbalanced flow line

Critical WIP loops II (CWIPL II) is a proposed material flow control mechanism for an unbalanced flow line environment. CWIPL II is based on CWIPL and it determines critical loops in unbalanced lines. The WIP of critical loops identifies the time of releasing raw material to the line. CWIPL II proposed a new classification for unbalanced flow line which is ‘near unbalanced flow line’ and ‘perfect unbalanced flow line’. In near unbalanced line, there is one bottleneck and a raw material release to the line if ‘WIP of the bottleneck’ or ‘WIP upstream the bottleneck’ is less than defined level. In perfect unbalanced line there are multiple bottleneck and a raw material release to the line if ‘WIP upstream the slowest machine’ or ‘WIP between two primary bottleneck’ is less than defined level. Like CWIPL, the necessary condition for releasing the raw material is ‘idleness of the first machine’. CWIPL II is compared with CONWIP and TOC by simulation. Different scenarios are employed in the comparison analysis. The scenarios address variables such as number of machines, processing time distribution, WIP target level. Location of slowest machine and location of two primary bottlenecks are considered in examples. Simulation results and statistical tests of 141 numerical examples show that CWIPL II improves lead time in near unbalanced line and throughput in perfect unbalanced line compared with TOC. Because of the trade off between line throughput and lead time, the mechanism that improves one of them while maintaining the other at previous level is valuable. It is shown that CWIPL II has improved TOC in the cases that TOC hasn’t improved CONWIP.