The shift team formation problem in multi-shift manufacturing operations

This paper addresses the problem of assigning operators to teams that work in single-, two-, or three-day shift systems. The problem was motivated by, and illustrated with a case situation encountered in Dutch manufacturing industry. The problem addressed forms an extension of cell formation problems which are currently in the phase of addressing labor-related issues in cell design. A generalized goal problem formulation is presented to address multiple, conflicting objectives covering cross-training of workers, ensuring adequate levels of labor flexibility and minimizing labor-related costs. The proposed solution procedure consists of two phases. In the first phase, shift systems, in which applicable machines and the sizes of each shift team are identified. The next phase deals with assignment of operators to various teams and identification of specific cross-training needs for various workers. This phase involves the use of interactive goal programming. The methodology is illustrated by details from the case situation as well as a numerical example.

Production planning under dynamic product environment: a multi-objective goal programming approach

Production planning is a complicated task that requires cooperation among multiple functional units in any organization. In order to design an efficient production planning system, a good understanding of the environment in terms of customers, products and manufacturing processes is a must. Although such planning exists in the company, it is often incorrectly structured due to the presence of multiple conflicting objectives. The primary difficulty in modern decision analysis is the treatment of multiple conflicting objectives. A formal decision analysis that is capable of handling multiple conflicting goals through the use of priorities may be a new frontier of management science. The objective of this study is to develop a multi objective goal programming (MOGP) model to a real-life manufacturing situation to show the trade-off between different some times conflicting goals concerning customer, product and manufacturing of production planning environment. For illustration, two independent goal priority structures have been considered. The insights gained from the experimentation with the two goal priority structures will guide and assist the decision maker for achieving the organizational goals for optimum utilization of resources in improving companies competitiveness. The MOGP results of the study are of very useful to various functional areas of the selected case organization for routine planning and scheduling. Some of the specific decision making situations in this context are: (i). the expected quality costs and production costs under identified product scenarios, (ii).under and over utilization of crucial machine at different combinations of production volumes, and (iii). the achievement of sales revenue goal at different production volume combinations. The ease of use and interpretation make the proposed MOGP model a powerful communication tool between top and bottom level managers while converting the strategic level objectives into concrete tactical and operational level plans.

Flexible automation and the loss of pooling synergy

This paper focuses on the effects of flexible automation on the performance of a job shop. Flexible automated machines may significantly improve the delivery performance and the flow time of jobs. The insertion of a flexible automated system in a job shop, however, also has a counter effect on the manufacturing performance. This is caused by the reduction of pooling synergy due to the dedication implied by flexible automated machines. This paper investigates by means of a simulation study to what extent the loss of pooling synergy will deteriorate job shop performance. Simulation is also used to indicate the level of efficiency of the automated machinery needed to overcome the negative effect of the loss of pooling synergy. The simulation study also highlights the importance of appropriate off-line assignment rules, which assign jobs to either the conventional or automated machines. Major conclusion of this paper is that the ‘pooling loss effect’ should be taken into account in the design and justification of new flexible automated machinery. The design of appropriate offline assignment rules, furthermore, has to be seen as an integral part of investment in new technology.

Assessing to what extent smart manufacturing builds on lean principles

This study explores to what extent the adoption and performance of smart manufacturing technologies builds on the adoption of lean principles. Primary explorative survey data on the level of adoption of smart manufacturing technologies and lean principles and various operational performance outcomes were collected from a set of Dutch manufacturers and analysed using Cluster Analysis, ANOVA, and Necessary Condition Analysis (NCA). The Cluster Analysis shows that while lean is also applied without smart (“lean-only” companies), smart technologies are mostly applied in conjunction with lean (“lean and smart” companies), suggesting that the presence of lean principles is necessary for smart implementation. A third group of companies shows a low use of lean and smart (“non-adopters”). The NCAs further specify the extent of this necessity by showing that all individual smart manufacturing technologies used in our construct require presence of lean principles, with MES systems having the strongest dependency. Performance wise, lean-only and lean and smart companies have comparable superior performance compared to non-adopters when considering an aggregate operational performance measure using the dimensions of quality, delivery, flexibility and cost. When analysed separately, the aggregate level results remain true for quality and delivery performance. However, for flexibility, the superiority of lean-only companies is more apparent, while for cost, lean and smart companies are superior. This shows that implementing smart requires lean, but lean may suffice depending on the specific performance objectives strived for

Impact of lean interventions on time buffer reduction in a hospital setting

This paper focuses on performance changes stemming from a series of lean interventions in a medical laboratory. This research is one of the first to link a series of lean interventions and performance over time. In a mixed-method case study, six years of patient-related throughput data, retrieved from a laboratory computer database, are analysed. Three distinct periods with significant differences in throughput time performance can be distinguished. Semi-structured interviews were held to investigate the lean interventions preceding the performance changes. Given the long-term nature of the study, the event history calendar method was applied to enhance the respondents' recall and reliability. A single lean intervention, among the hundreds that took place, was supposed to cause the main reduction in throughput times. It concentrated on improving process flow through the removal of batching, a source of artificial variability. A later major intervention, the introduction of flow-focused machinery, had mixed effects and initial performance gains were not sustained. The results show that ongoing series of interventions do not always lead to ongoing performance improvements in terms of throughput times but support theories emphasising the importance of variability reduction