Dual Resource Constrained Systems Research Articles

Worker Assignment in Dual Resource Constrained Systems Subject to Machine Failures: A Simulation Study

Worker Assignment in Dual Resource Constrained Systems Subject to Machine Failures: A Simulation Study

A game theory model based on Gale-Shapley for dual-resource constrained (DRC) flexible job shop scheduling

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.

Production planning in DRC systems considering worker performance

This paper studies the effects of some human characteristics on production planning in a Dual-Resource Constrained (DRC) system and the quality of products. Human behavior is captured by the learning–forgetting–fatigue–recovery model (LFFRM). The production process is modeled through a Quality Learning Curve (QLC) model while the quality deficits are the result of human error and machine malfunction. The system performance is presented with a twofold cost function considering direct (time) and indirect (quality) costs. The results indicate that the system performance is concave over a production run, which represents the optimum flexibility level, transfer policy, and the workstation configuration.

Agent-based modelling of movement rules in DRC systems for volume flexibility: human factors and technical performance

This research applies agent-based modelling (ABM) to study volume flexibility in a dual resource constrained (DRC) assembly flow shop environment. The simulation experiment evaluated system and human effects of varying DRC system staffing levels according to design (i.e., workforce, distance and buffer capacity), sensitivity (i.e. coefficient of variation) and operating (i.e. when rule and where rule) factors. Results showed that the rule by which workers are assigned to workstations affects WIP and flow time performances more than production rates. Furthermore per-worker productivity was found to increase, compared to the fully staffed system, particularly where the downstream movement rule was applied. Using the downstream rule when changing stations after completing current tasks reduced flow time (−15%) and WIP (−10%). If another where rule is chosen then it may be preferable for workers to move only after completing all jobs in the station (decentralised rule). For utilisation rates and mean hourly switching of work (human effects), the model shows complex relationships depending on almost all evaluated factors. The novel ABM approach used here enabled the evaluation of emergent system behaviours and showed potential to help firms understand both human and performance effects of operational choices in efforts to achieve volume flexibility.

Recent developments in Dual Resource Constrained (DRC) system research

Real world manufacturing systems are usually constrained by both machine and human resources. Human operators are often the constraining resource and transfer between workstations to process jobs when required. This kind of system is known as a Dual Resource Constrained (DRC) system and presents additional technical challenges which must be considered during planning and scheduling. These technical challenges can be categorised into the five main dimensions of job release mechanisms, job dispatching, worker flexibility, worker assignment and transfer costs. This paper aims to provide an overview of recent developments in DRC research concerned with each of these areas and also discusses some possible approaches to solving the resource scheduling problem in a DRC system. The focus is on materials published after 1995 and up to 2009. Previous reviews on DRC systems are commented on and followed by a review of recent works associated with each of the five dimensions of DRC system research. Advancements made and new methodologies proposed are discussed and future research directions are identified.

Modelling worker fatigue and recovery in dual-resource constrained systems

The operational benefits that dual-resource constrained (DRC) job shop systems bring have captured the attention of researchers for some time. Although several studies that investigate DRCs are available in the literature, none has investigated a DRC system for the effects of human fatigue and recovery, which poses important parameters to avoiding overload and injury to employees. The purpose of this paper is to address this limitation by presenting a mixed-integer linear programming (MILP) model that describes fatigue and recovery in a DRC system with one worker performing n tasks (flexibility level) within m cycles. Later, the complexity of the MILP problem was reduced to four practical cases. These cases were investigated to evaluate several research questions. The results obtained from the MILP model and the four practical cases suggest that short rest breaks after each task, short cycle times and faster recovery rates improve the system’s performance and that reduced force levels in the work tasks will reduce recovery needs and further increase performance. Further research is still needed to identify or to develop better models of physiological and mental fatigue that can be integrated to the modelling framework presented here.

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.

A multi-criteria adaptive control scheme based on neural networks and fuzzy inference for DRC manufacturing systems

Manufacturing systems are uncertain and dynamic systems, hence, they require real-time scheduling to adapt to changing manufacturing conditions. Current real-time scheduling approaches have been devised mainly for machine-only constrained systems, in which the shop capacity is constrained only by machine capacity, rather than for dual resource constrained (DRC) systems, in which the shop capacity is constrained by machine and worker capacity. In particular, there is no study on DRC system scheduling in which the ‘where’ and ‘when’ worker assignment rules, basic features of DRC systems, are altered in real-time (dynamically selected) to respond to new manufacturing conditions. Besides, multi-criteria DRC system scheduling has not yet been addressed extensively. Also, there has been little research on the interactions of dynamically selected job dispatching, worker assignment and job routing rules, which have a significant impact on DRC system performance. This paper proposes a multi-criteria real-time scheduling methodology for DRC systems to address these issues, and investigates these interactions. The methodology employs artificial neural networks as meta-models to reduce computational complexity and a fuzzy inference system to cope with multiple performance criteria. Various simulation experiments demonstrate that the methodology provides satisfactory results for real-time DRC systems scheduling.

Worker deployment in dual resource constrained systems with a task-type factor

This paper investigates worker learning and forgetting phenomenon in a dual resource constrained system (DRC) setting. Worker learning and forgetting in two and three stage DRC systems are modeled according to the dual-phase learning and forgetting model (DPLFM), which is based on the theory that a task has separate cognitive and motor requirements. Results show that the task-type (with respect to its learning rate and proportion of cognitive and motor requirements) affects the performance of training and deployment policies in DRC systems, and as such it should be included in future DRC research.

Response surface methodology based simulation optimization of a CONWIP controlled dual resource constrained system

We propose an optimal worker flexibility policy for a CONWIP (constant work-in-process) controlled dual resource constrained (DRC) system. A critical issue in DRC systems is the dynamic assignment of workers to the workstations. The proposed worker flexibility policy is designed to evaluate the state of the system at periodic time intervals so that the dynamic assignment of workers to the workstations can be made in an efficient manner. By integrating the response surface methodology (RSM) with simulation, this study provides an approach for optimizing worker transfer decisions. The RSM-based simulation optimization approach adopted in this study provides an effective and robust procedure to determine the optimum level of this decision variable under the given operating conditions.

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.

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.

Modeling simultaneous worker learning and forgetting in dual resource constrained systems

This paper addresses issues related to modeling worker learning and forgetting effects in Dual Resource Constrained (DRC) systems. The learn-forget-learn (LFL) model of Carlson and Rowe (Carlson, J.C., Rowe, A.J., 1976. Industrial Engineering 8, 40–47) is used to critically evaluate several worker training related issues that are associated with the learning and forgetting phenomenon. A numerical analysis is performed on the LFL model within a DRC system to gain insights into the nature of relationships between the extent of worker flexibility, forgetting rates, attrition rates, and flexibility acquisition policies. Results suggest that in the presence of higher attrition and forgetting rates, a worker may not be able to achieve full efficiency in as little as two different departments. Thus acquiring even incremental worker flexibility under such conditions may be infeasible. We also show that managers can use different flexibility acquisition policies designed in this study to reduce relearning losses and consequently improve the system performance.

An evaluation of worker assignment policies in dual resource-constrained job shops with heterogeneous resources and worker transfer delays

Abstract The focus of this study is on investigating worker assignment policies in dual resource constrained (DRC) job shops which include features such as the presence of heterogeneous resources and worker transfer delays between different departments. Previous studies on DRC systems have not modelled a shop which includes these design features simultaneously, although both of them would be present in many actual DRC environments. Several worker assignment policies that can be expected to work well in such environments are proposed and tested. Results indicate that in most DRC shops that have heterogeneous resources and finite transfer delays, decentralized assignments which delay the transfer decisions improve system performance. Additionally, two different task selection rules are shown to be very robust in giving good performance across a wide range of DRC environments modelled in the study.

A Review of the Dual Resource Constrained System Research

Abstract This paper reviews the recent dual resource constrained (DRC)system literature. The DRC system research has gained new significance through the emphasis being placed on cross-training by Just-In-Time (JIT) system advocates. Cross-training is the key to labor flexibility-one of the key issues in the DRC system research. This review covers over twenty-five articles about DRC systems and should be helpful in familiarizing potential DRC system researchers with the field. The DRC system research and results, categorized into design and operating decisions, are summarized and suggestions for future research are provided. A table which summarizes the characteristics of the DRC systems modeled, decision rules examined, statistical analysis methods employed, and the performance criteria used in each study is also provided. An appendix is used to highlight characteristics that are common to many of the models employed in the studies surveyed.