Academic journal article Human Factors

A New Model of Scheduling in Manufacturing: Tasks, Roles, and Monitoring

Academic journal article Human Factors

A New Model of Scheduling in Manufacturing: Tasks, Roles, and Monitoring

Article excerpt


There are few areas in life in which scheduling does not play a part. Scheduling is a fundamental process that is essential within business, industry, and service sectors. There are numerous forms of scheduling--for example, devising personnel rosters, train and aircraft timetables, and administrative timetables, as well as production scheduling. This paper focuses on the domain of production scheduling. In its simplest form, a production schedule is a list or sequence of work that needs to be completed. The objective of the scheduling process is to set the priorities of the work and the allocation of resources to achieve this. A typical definition of scheduling that reflects this view is the goal-directed allocation of resources over time to perform a collection of tasks (Baker, 1974; Morton & Penrico, 1993; Ovacik & Uzsoy, 1997; Pinedo, 1995; Sadowski & Medeiros, 1982).

Taking this perspective, schedule generation appears to be an optimization and prioritization problem. This classic operations research perspective of the function underpins many previous research solutions for the scheduling problem, building mathematically tractable models using specific algorithms to solve scheduling scenarios. However, the majority of derived mathematical solutions have not been used in practice by manufacturing businesses (MacCarthy & Wilson, 2001). To businesses, such models are static and appear to ignore the complexity of the real world, in which scheduling is both dynamic and ill defined (Stoop & Wiers, 1996).

The sheer volume of published research on classical scheduling theory, as noted by Dessouky, Moray, and Kijowski (1995), demonstrates that scheduling researchers are still searching for models of scheduling that can provide realistic business solutions. Most of this type of research simply adopts the mathematical approach and ignores the significant human contribution to scheduling. However, the study of practice, upon which this paper is based, demonstrates the limitations of this purely computational perspective of scheduling.

This paper draws from a program of research that focused on the investigation and implementation of scheduling performance (Crawford, MacCarthy, Wilson, & Vernon, 1999: MacCarthy & Wilson, 2001; MacCarthy, Wilson, & Crawford, 2001). The underlying research assumption was straightforward: Researchers should focus on how scheduling is actually carried out in order to understand what scheduling is and how it occurs in practice. The overall aim was to develop a descriptive model of scheduling performance that would capture scheduler behavior and performance in order to underpin the development of scheduling systems that would be more appropriate than those based on previous theoretical scheduling models.

We begin by identifying the need for a new model of scheduling, using evidence from previous research on models of the human scheduler. Our research derives from a naturalistic decision making (NDM) perspective (Klein, Orasanu, Calderwood, & Zsambok, 1993: Lipshitz. Klein, Orasanu, & Salas, 2001). The nature of the study, the research approach, and methods used to conduct the field studies and to derive the model are first presented, and this is supported by an overview of the participant schedulers. The main contribution of the paper centers on the development of a new model of scheduling in manufacturing. The implications and potential applications of the model in practice conclude the paper.


Some previous research has exposed the field of scheduling research to consideration of context and actual working environments: a full review of this field of research is presented in Crawford and Wiers (2001). Here we concentrate on research that has attempted to develop models of human scheduling in manufacturing contexts.

Sanderson (1991) proposed a model human scheduler as a descriptive, computational model that could support the design decisions needed in advanced manufacturing systems and improve understanding of the human contribution to scheduling functions. …

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