Human, technological and organizational aspects influencing the production scheduling process

Berglund, Martina; Karltun, Johan

doi:10.1016/j.ijpe.2007.02.024

Cited by 77 publications

(90 citation statements)

References 10 publications

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“…There are case studies in which it is reported that less than 50% of the required data were consistent (see Leachman et al, 1996). Poor data quality is frequently mentioned (see Berglund and Karltun, 2007) as the cause that specific tools and spreadsheets have to be used to complement standard scheduling software tools, and as an explanation of the failure of some scheduling tools' implementations (see Pinedo, 2007). Indeed, one of the tasks of the human scheduler is to filter the data to be employed in the scheduling process (MacCarthy and Wilson, 2001).…”

Section: Data Qualitymentioning

confidence: 99%

Guidelines for the deployment and implementation of manufacturing scheduling systems

Framiñán

Ruíz

2012

International Journal of Production Research

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It has been frequently stated that there exists a gap between production scheduling theory and practice. In order to put the theoretical findings into practice, the advances in scheduling models and solution procedures should be embedded into a piece of software -a scheduling system-at work in the companies. This results in a process which entails 1) determining its functional features, and 2) adopting a successful strategy for its development and deployment. In this paper we address the latter question and review the related literature in order to identify descriptions and recommendations of the main aspects to be taken into account when developing such system. These issues are then discussed and classified, resulting in a set of guidelines that can help practitioners during the process of developing and deploying a scheduling system. In addition, the identification of these issues can provide some insights to drive the theoretical scheduling research towards those topics more demanded by practitioners, thus helping in closing the aforementioned gap.

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Section: Data Qualitymentioning

confidence: 99%

Guidelines for the deployment and implementation of manufacturing scheduling systems

Framiñán

Ruíz

2012

International Journal of Production Research

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“…This scheduler has to evaluate and assess the effect of the event, and probably has to adapt schedule constraints to enable the recreation of a feasible schedule. This indispensable role of the human planner during rescheduling has been shown in several empirical studies (Berglund and Karltun 2007;Fransoo and Wiers 2006;Jackson et al 2004;MacCarthy and Wilson 2001;McKay et al 1995a). One important task for the scheduler is to determine if an event has to be resolved individually or if it requires coordination with fellowschedulers, managers, foremen, or operators.…”

Section: Introductionmentioning

confidence: 96%

Coordination activities of human planners during rescheduling: case analysis and event handling procedure

Snoo

Wezel

Wortmann

et al. 2011

International Journal of Production Research

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“…As discussed in the previous section, the design of a scheduling algorithm is mainly related to stages 2 and 3 of Mitroff"s problem-solving model (figure 1). As it has been observed, scheduling algorithms designed through the traditional production research approach are rarely favored to ad-hoc approaches in realistic industrial environments (Berglund and Karltun, 2005). This section examines in detail the traditional approach provides a critical review of its shortcomings.…”

Section: Designing Algorithms For Scheduling Problems: a Critical Reviewmentioning

confidence: 99%

“…As it has been discussed by various researchers, the traditional production research approach to the design of scheduling algorithms has rarely made an impact in realistic industrial environments (Portougal and Robb, 2000;Fransoo and Wiers, 2005), (Berglund and Karltun, 2005). In practice, the majority of schedulers assume full control of the scheduling process by employing ad-hoc solution approaches.…”

Section: The Scheduling Environment: the Traditional Production Reseamentioning

confidence: 99%

Design of Scheduling Algorithms

Riezebos

Hoc

Mebarki

et al. 2010

Behavioral Operations in Planning and Scheduling

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The academic field of production research has been growing rapidly over the last decades with researchers proposing numerous analytical and heuristic optimization methodologies for the solution of planning & scheduling problems. However, adaption by manufacturing companies is lagging behind. This paper suggests that the basic reason behind this imbalance is the inadequate representation of the planning & scheduling process when designing decision support systems. Hence, the algorithms that are designed and included in these systems might not reflect the problems that actually have to be solved in practice. In this paper we discuss the basic factors that are important for the development of planning & scheduling decision support systems. These factors will be based on insights from cognitive psychology, computer science, and operations management.Keywords: scheduling, algorithms, cognitive science INTRODUCTIONThe accomplishment of a manufacturing company"s objectives is strongly connected to the efficient solution of complex scheduling problems that are faced in the production environment. The academic field of production research has been growing rapidly over the last decades with researchers proposing numerous analytical and heuristic optimization methodologies for the solution of scheduling problems (Slack et al., 2004). However, very few of them have been extensively adopted by manufacturing companies. The basic reason behind this imbalance is the inadequate representation of the very complex scheduling process, as this is implemented in practice.The main aim of this chapter is to provide a theoretical discussion on the design of scheduling algorithms. In the first part of this discussion a detailed description of the general problem-solving process will be presented. The second part will concern a critical review of traditional production research algorithmic design approaches. This review will contrast the model of the scheduling environment as this is conceived by traditional production research approaches against models that specifically address human and organizational issues. The final part of this chapter builds on the discussion of the previous sections and proposes the development of a scheduling theoretical framework. This framework will help practitioners to design decision support tools that specifically address human and organizational considerations of the scheduling case considered.

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Human, technological and organizational aspects influencing the production scheduling process

Cited by 77 publications

References 10 publications

Guidelines for the deployment and implementation of manufacturing scheduling systems

Guidelines for the deployment and implementation of manufacturing scheduling systems

Coordination activities of human planners during rescheduling: case analysis and event handling procedure

Design of Scheduling Algorithms

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