Jos Bokhorst

A lean production control system for high-variety/low-volume environments: a case study implementation

Due to the success of lean manufacturing, many companies are interested in implementing a lean production control system. Lean production control principles include the levelling of production, the use of pull mechanisms and takt time control. These principles have mainly been applied in high volume flow shop environments where orders move through the production system in one direction in a limited number of identifiable routing sequences. This article investigates how lean production control principles can be used in a make-to-order job shop, where volume is typically low and there is high variety. We show how production levelling, constant work in process, first in first out and takt time can be integrated in a lean production control system. A case study is presented to illustrate the design and phased implementation of the system in a typical dual resource constrained production environment. The case study demonstrates that lean production control principles can be successfully implemented in a high-variety/low-volume context. Implementation led to a reduction in flow times and an increase in the service level achieved, with on-time delivery performance improving from 55 to 80%.

Condition based maintenance in the context of opportunistic maintenance

Condition based maintenance (CBM) uses the operating condition of a component to predict a failure event. Compared to age based replacement (ABR), CBM usually results in higher availability and lower maintenance costs, since it tries to prevent unplanned downtime and avoid unnecessary preventive maintenance activities for a component. However, the superiority of CBM remains unclear in multi‐component systems, in which opportunistic maintenance strategies can be applied. Opportunistic maintenance aims to group maintenance activities of two or more components in order to reduce maintenance costs. In a serial system, this may also result in less downtime of the production line. The aim of this paper is to examine the impact of opportunistic maintenance on the effectiveness of CBM. We simulate a small system consisting of three components in series and vary the number of components under a CBM policy, the length of the opportunistic maintenance zone, the cost benefits of grouping maintenance activities, and the chance of a failure occurrence within a preventive maintenance (PM) interval. The results show that within the current experimental settings, CBM remains cost effective in the multi‐component serial system, but is less effective than ABR in grouping maintenance activities. When the chance of failure is small and the length of the opportunistic maintenance zone is large, ABR may even be a better option if line productivity is important.

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.

The influence of condition-based maintenance on workforce planning and maintenance scheduling

Condition-based maintenance (CBM) is generally considered an attractive maintenance policy for a single component: it uses the operating condition of the component to predict a failure event and therefore tries to avoid any unplanned downtime and unnecessary maintenance activities. However, operations managers tend to be much more interested in optimising the performance of the entire asset-system, where the grouping of maintenance activities and the availability of maintenance workers may play a role. Therefore, this paper focuses on the impact of using either CBM or age-based replacement (ABR) in serial and parallel multi-component systems (1) without worker constraints, (2) with a single internal maintenance worker, and (3) with external maintenance workers with a significant response time. With an internal maintenance worker, the sequential execution of maintenance activities prevents efficiency gains in the serial configuration and here CBM performs better. Also in the parallel configurations, the efficiency under CBM is generally better than under ABR. However, with external maintenance workers, CBM is not able to group maintenance activities as well as ABR, which results in a lower efficiency in the serial configuration. CBM performs better than ABR with respect to total maintenance costs, while ABR results in a smoother maintenance plan.

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.

An integrated model for part-operation allocation and investments in CNC technology

Abstract This study addresses the issue of investment appraisal of new technology, specifically computer numerical control (CNC) machine tools in conjunction with optimal allocation of parts and operations on CNC machines as the investments take place. Part-operation allocation is the allocation of parts and operations to either the conventional machines or to the new technology as they are acquired. It is shown that part allocation is an important consideration in the assessment of profitability from investments in CNC technology. A mixed integer programming model is presented to (1) determine the optimal allocation of parts and operations to conventional machines and to new CNC machine tools; and (2) determine the optimal investment sequence and timing of investments in CNC machine tools. The optimality criterion is based on a maximization of net present value (NPV) over a specified planning horizon. The application of the model is illustrated using a numerical example, and the implications for industrial practice are also indicated.

Performance evaluation of family-based dispatching in small manufacturing cells

In many practical instances, the choice of whether to apply family-based dispatching or not can be decided per machine. The present paper explores the impact of the location of family-based dispatching, load variations between machines and routing of jobs on the flow time effect of family-based dispatching. These factors are explored in small manufacturing cells with and without labour constraints. An industrial case motivates the study. A simulation study is performed to assess the impact of these effects. The results show that shop-floor characteristics such as routing and load variation impact the decision where to locate family-based dispatching in manufacturing cells without labour constraints. By contrast, the effect of family-based dispatching is much less vulnerable to shop-floor characteristics in cells with labour constraints. Since workers are the bottleneck in these cells, it becomes less important at what machine the set-up time involving a worker is reduced. In general, there seems to be a trade-off between the positive effect of applying family-based dispatching at a (bottleneck) machine and the possible negative effect of the more irregular job arrivals at subsequent machines. The results further indicate that family-based dispatching is more advantageous in cells with labour constraints than in cells without labour constraints, when both types of manufacturing cells have comparable machine utilizations.

The impact of the amount of work in process on the use of cross-training

Cross-training is becoming increasingly important to firms in order to cope with the more stringent performance requirements they are faced with in todays market. However, many firms put considerable effort into cross-training their workers only to find out that their workers favour the familiar tasks and hardly use and maintain the newly acquired skills. In this paper we explore the hypothesis that reducing the amount of work in process in a constant work in process (CONWIP) controlled job shop with worker preferences forces workers to make a more balanced use of the skills they possess. We test this hypothesis by means of a simulation study with the level of cross-training as moderating variable. Based on this study, it can be concluded that the control and limitation of the amount of work in process breaks the pattern of workers remaining at their preferred machines and constrains the workers to use and maintain their other skills more.

Cooperation in a distributed dual resource-constrained manufacturing system

In this paper, we distinguish two types of cooperation between distributed manufacturing cells to deal with variations in the request for manufacturing capacity between cells. Load-oriented Cooperation (LC) concerns the reallocation of jobs to different cells. Resource-oriented Cooperation (RC) refers to movements of workers between cells. We investigate the effect of these types of cooperation on manufacturing performance by means of a simulation study. Major outcome of our study is that the maximal effect of LC is higher than the maximal effect of RC. Furthermore, our study indicates that a high level of LC may absorb all positive effects of RC. However, RC remains relevant in case of low levels of LC. LC remains profitable, even in case of a maximal level of RC. Our study also shows that increased labour utilization magnifies the effect of a first introduction of some cooperation.

Impact of Technology on Work: Technical Functionalities that Give Rise to New Job Designs in Industry 4.0

Manufacturing firms are constantly evolving to accommodate new customer requirements as well as emerging technologies, materials, processes and equipment. As a consequence, a broad range of production innovation opportunities arise for manufacturing firms to produce their products in smarter, more flexible, agile and sustainable ways. This paper proposes a strategic planning framework for “production innovation” and discusses its implications for the evolution of companies-specific production systems and competitive advantages.