Eric H. Grosse and Christoph H. Glock
The purpose of this paper is to study the prevalence of human learning in the order picking process in an experimental study. Further, it aims to compare alternative learning…
Abstract
Purpose
The purpose of this paper is to study the prevalence of human learning in the order picking process in an experimental study. Further, it aims to compare alternative learning curves from the literature and to assess which learning curves are most suitable to describe learning in order picking.
Design/methodology/approach
An experimental study was conducted at a manufacturer of household products. Empirical data was collected in the order picking process, and six learning curves were fitted to the data in a regression analysis.
Findings
It is shown that learning occurs in order picking, and that the learning curves of Wright, De Jong and Dar‐El et al. and the three‐parameter hyperbolic model are suitable to approximate the learning effect. The Stanford B model and the time constant model led to unrealistic results.
Practical implications
The results imply that human learning should be considered in planning the order picking process, for example in designing the layout of the warehouse or in setting up work schedules.
Originality/value
The paper is the first to study learning effects in order picking systems, and one of the few papers that use empirical data from an industrial application to study learning effects.
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T.K. Bhattacharjee and S. Sahu
This paper briefly reviews the assembly line balancing techniques developed over the last 30 years. It attempts to establish the direction of research, to identify unexplored…
Abstract
This paper briefly reviews the assembly line balancing techniques developed over the last 30 years. It attempts to establish the direction of research, to identify unexplored areas with potential for study and recommends future courses of action.
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Some of the conventions regarding relearning of complex tasks (requiring both psychomotor and procedural skills) are well known, especially as relating to retention curves. Still…
Abstract
Some of the conventions regarding relearning of complex tasks (requiring both psychomotor and procedural skills) are well known, especially as relating to retention curves. Still lacking, however, is information which better clarifies the relationship between relearning and skill retention. The purpose of this study was to examine this relationship while identifying the parameter affecting the duration between training intervals, in order to maintain a high level of performance. Two additional aspects were examined in this study: actual differences in the measure of decrease in the operator’s level for various task dimensions and the implication for integrating a simulator in the refresher training program. This study conducted a controlled field experiment in a military electronic warfare unit, examining refresher training of reserve soldiers operating a complex electronic system. Examination of the study’s hypotheses and analysis of the experiment’s results indicated a cyclical behavioral model of the retention curve and the relearning aspects involved (training intervals, “warming up” phenomenon, model boundaries etc.). This result necessitates the inclusion of the retention curve within the framework of the instruction task analysis (especially with training programs which include refresher training). It should be noted that the study’s conclusions are valid not merely for military tasks, but are also valid for implementation in complex civilian tasks.
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Mario Tabucanon and Wang Changli
Outlines the specific characteristics of semiautomatic productionlines which, in relative terms, are given less attention than othertypes of line. Suggests a methodology for…
Abstract
Outlines the specific characteristics of semiautomatic production lines which, in relative terms, are given less attention than other types of line. Suggests a methodology for balancing such lines, making comparison thereof with the traditional method of line balancing. Applies the method to a case which is a typical semiautomatic line.
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Ezey M. Dar‐El and Gedaliahu H. Harel
This article describes a new approach to organisational development — one which integrates a management development programme with a worker development programme. The latter uses…
Abstract
This article describes a new approach to organisational development — one which integrates a management development programme with a worker development programme. The latter uses the Work Improvement Team (WIT) as its vehicle. Aspects of WIT functions, organisation and maintenance are discussed. The article stresses the how aspect of the development methodology and illustrates the process with studies made in two medium‐sized manufacturing plants.
Walking-worker assembly lines can be regarded as an effective method to achieve the above-mentioned characteristics. In such systems, workers, following each other, travel…
Abstract
Purpose
Walking-worker assembly lines can be regarded as an effective method to achieve the above-mentioned characteristics. In such systems, workers, following each other, travel workstations in sequence by performing all of the required tasks of their own product. As the eventual stage of assembly line design, efforts should be made for capacity adjustments to meet the demand in terms of allocating tasks to workers via assembly line balancing. In this context, the purpose of this study is to address the balancing problem for multi-model walking-worker assembly systems, with the aim of improving planning capability for such systems by means of developing an optimization methodology.
Design/methodology/approach
Two linear integer programming models are proposed to balance a multi-model walking-worker assembly line optimally in a sequential manner. The first mathematical programming model attempts to determine number of workers in each segment (i.e. rabbit chase loop) for each model. The second model generates stations in each segment to smooth workflow. What is more, heuristic algorithms are provided due to computational burden of mathematical programming models. Two segment generation heuristic algorithms and a station generation heuristic algorithm are provided for the addressed problem.
Findings
The application of the mathematical programming approach improved the performance of a tap-off box assembly line in terms of number of workers (9.1 per cent) and non-value-added time ratio (between 27.9 and 26.1 per cent for different models) when compared to a classical assembly system design. In addition, the proposed approach (i.e. segmented walking-worker assembly line) provided a more convenient working environment (28.1 and 40.8 per cent shorter walking distance for different models) in contrast with the overall walking-worker assembly line. Meanwhile, segment generation heuristics yielded reduction in labour requirement for a considerable number (43.7 and 49.1 per cent) of test problems. Finally, gaps between the objective values and the lower bounds have been observed as 8.3 per cent (Segment Generation Heuristic 1) and 6.1 (Segment Generation Heuristic 2).
Practical implications
The proposed study presents a decision support for walking-worker line balancing with high level of solution quality and computational performance for even large-sized assembly systems. That being the case, it contributes to the management of real-life assembly systems in terms of labour planning and ergonomics. Owing to the fact that the methodology has the potential of reducing labour requirement, it will present the opportunity of utilizing freed-up capacity for new lines in the start-up period or other bottleneck processes. In addition, this study offers a working environment where skill of the workers can be improved within reasonable walking distances.
Originality/value
To the best knowledge of the author, workload balancing on multi-model walking-worker assembly lines with rabbit chase loop(s) has not yet been handled. Addressing this research gap, this paper presents a methodology including mathematical programming models and heuristic algorithms to solve the multi-model walking-worker assembly line balancing problem for the first time.
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Antonio C. Caputo and Pacifico M. Pelagagge
The paper's aim is to assess the impact of product related features on the performances of assembly line manufacturing systems, also providing a specific Design for Manufacturing…
Abstract
Purpose
The paper's aim is to assess the impact of product related features on the performances of assembly line manufacturing systems, also providing a specific Design for Manufacturing and Assembly rating index to assess the goodness of a product design solution with respect to assembly line performances.
Design/methodology/approach
A computer simulation‐based parametric analysis was carried out to assess the impact of four major product‐related parameters. 216 different assembly line balance problem instances were evaluated. Findings allowed to develop a DFMA rating index specific for assembly line manufacturing as well as design guidelines.
Findings
Assembly sequence degrees of freedom and the ratio of the average task duration to the maximum duration are the most influencing parameters. While the former should be maximized, only a moderate task duration variability was found beneficial. The influence of other factors resulted less marked and changing on a case‐specific basis.
Research limitations/implications
Complex interactions between product design features and line performances prevent generalization. The performed numerical experimentation, although extensive, remains somewhat limited respect all possible practical situations. The proposed rating index should be utilized while maintaining an overall perspective about the mutual influence of all parameters. Some suggested guidelines imply a trade off with traditional DFMA guidelines.
Practical implications
Product designers are given useful insights, tools and guidelines to develop better producible products. With the proposed ranking index a designer can easily rate his choices when selecting assembly tasks and sequences, as well as rank alternative product designs solutions.
Originality/value
The paper presents an original discussion about the impact of product design choices on assembly line performances. The developed DFMA rating index and guidelines are new.
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Fabio Sgarbossa, Christoph H. Glock, Eric H. Grosse, Martina Calzavara and René de Koster
In manual order picking systems, temporary workers are often employed to handle demand peaks. While this increases flexibility, it may hamper productivity, as they are usually…
Abstract
Purpose
In manual order picking systems, temporary workers are often employed to handle demand peaks. While this increases flexibility, it may hamper productivity, as they are usually unfamiliar with the processes and may have little experience. It is important for managers to understand how quickly inexperienced workers arrive at full productivity and which factors support workers in improving their productivity. This paper aims to investigate how learning improves the performance of order pickers, and how their regulatory focus (RF) and monetary incentives, as management actions, influence learning.
Design/methodology/approach
Data was collected in two case studies in controlled field-lab experiments and statistically analysed. This allowed evaluating the validity of hypotheses through an ANOVA, the calculation of correlation coefficients and the application of regression models.
Findings
A monetary incentive based on total order picking time and pick errors has a positive influence on order picking time, but not on pick quality. The incentive influences initial productivity, but not the learning rate. A dominant promotion-oriented RF increases the effect of the incentive on initial productivity, but it does not impact worker learning.
Practical implications
This study contributes to behavioral and human-focused order picking management and supports managers in setting up work plans and developing incentive systems for learning and productivity enhancement, considering worker RF.
Originality/value
This work is among the few to empirically investigate the effect of monetary incentives on learning in interaction with RF. It is the first study to investigate these concepts in an order picking scenario.
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Motivated by recent research indicating that the operational performance of an enterprise can be enhanced by building a supporting data-driven environment in which to operate…
Abstract
Purpose
Motivated by recent research indicating that the operational performance of an enterprise can be enhanced by building a supporting data-driven environment in which to operate, this paper presents a simulation framework that enables an examination of the effects of applying smart manufacturing principles to conventional production systems, intending to transition to digital platforms.
Design/methodology/approach
To investigate the extent to which conventional production systems can be transformed into novel data-driven environments, the well-known constant work-in-process (CONWIP) production systems and considered production sequencing assignments in flowshops were studied. As a result, a novel data-driven priority heuristic, Net-CONWIP was designed and studied, based on the ability to collect real-time information about customer demand and work-in-process inventory, which was applied as part of a distributed and decentralised production sequencing analysis. Application of heuristics like the Net-CONWIP is only possible through the ability to collect and use real-time data offered by a data-driven system. A four-stage application framework to assist practitioners in applying the proposed model was created.
Findings
To assess the robustness of the Net-CONWIP heuristic under the simultaneous effects of different levels of demand, its different levels of variability and the presence of bottlenecks, the performance of Net-CONWIP with conventional CONWIP systems that use first come, first served priority rule was compared. The results show that the Net-CONWIP priority rule significantly reduced customer wait time in all cases relative to FCFS.
Originality/value
Previous research suggests there is considerable value in creating data-driven environments. This study provides a simulation framework that guides the construction of a digital transformation environment. The suggested framework facilitates the inclusion and analysis of relevant smart manufacturing principles in production systems and enables the design and testing of new heuristics that employ real-time data to improve operational performance. An approach that can guide the structuring of data-driven environments in production systems is currently lacking. This paper bridges this gap by proposing a framework to facilitate the design of digital transformation activities, explore their impact on production systems and improve their operational performance.
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The purpose of this paper is to investigate the tradeoffs between efficiency and flexibility in production processes involve a cross-trained workforce. The study quantifies…
Abstract
Purpose
The purpose of this paper is to investigate the tradeoffs between efficiency and flexibility in production processes involve a cross-trained workforce. The study quantifies production losses that stem from worker learning and forgetting in a cross-training environment.
Design/methodology/approach
The paper examines multiple levels of cross-training in the context of several workplace factors including absenteeism, turnover, process change frequency, and process change magnitude using discrete event simulation. The parameters of the simulation model are informed by data from a operating manufacturing system.
Findings
Results suggest that productivity gains obtained from a moderate level of cross-training (e.g. two tasks) can outweigh the production losses from additional training, and that adding further cross-training beyond this may negatively affect system performance.
Originality/value
Production systems exist in an environment of process change and competitive pressure. Cross-training is an often-used operational technology for managing process knowledge in an environment of change as well as providing employees with a richer work environment. While the potential benefits of enriching the workplace experience include greater motivation, less boredom and fatigue, greater task vigilance, and other effects generally regarded as beneficial, productivity losses brought about by training and retraining disruptions associated with cross-training have not been examined as widely.