P. Broedner and W. Karwowski (Eds), Ergonomics Of Hybrid Automated Systems - III. Elsevier, 1992. pp. 211-216.
Human-Computer Production Scheduling: Contribution to the Hybrid Automation Paradigm
Peter G. Higgins School of Mechanical and Manufacturing Engineering, Swinburne Institute of Technology, P.O. Box 218 Hawthorn 3122, Australia (email
[email protected])
Abstract This paper reports on the development of an interactive system for opportunistic real-time dynamic production scheduling of small-batch manufacture.
1. INTRODUCTION A manufacturer of small-batches of discrete items is fortunate if its production is scheduled proficiently. Devising a good schedule takes talent. A well constructed schedule relies on an understanding of the capabilities of the resources and strategies for planning the sequence of operations. To plan the order of operations for jobs that make use of more than one resource can be rather complex. The number of combinations for sequencing operations easily extends beyond those that can be determined through exact mathematical solution. This conundrum is further compounded by the inclusion of contingencies. Some of these combinations appertain to the choice of routings, the priority of jobs, the constraints imposed on the order of operations (precedence constraints), the need to accelerate (expedite) the progress of some jobs, the presence of random failures, the availability of materials, and even changes to production goals. Defining a "good" schedule is formidable. Often multiple and disparate goals are sought. For example, a common objective is to minimise work-in-progress (WIP), and to maximise the utilisation of resources and service to customers (minimise lateness) [1]. But these individual goals conflict. For due dates to be routinely met resources have to be accessible without delay. For resources to be fully used, work has to be always available. This implies that there are jobs waiting, thereby conflicting with both the need for ready access and the minimisation of WIP. Some balance has to be found between the amount of WIP and the number of jobs that meet their due dates. Sometimes this balance is expressed as a cost function, which is problematic in itself. Furthermore the relative weights between goals tend to change over time.
Jobs waiting in queues at resources have to be arranged in some order that reflects their priority. Priorities are based either on their attributes (due date, customer, etc.) or system attributes (the conditions of the resources) or a combination of both. Many formalised rules have been developed for the setting of priorities. They are sub-optimal strategies for forward planning work based on the state of the system at the time the schedule was constructed. Different rules are applied for the satisfaction of different objectives. As contingencies arise, that divert the system's state from its predicted path, the schedule may drift further away from optimality. Various studies have sought ways to overcome the shortcomings in the application of these rules. Either the heuristics applied by real human schedulers were recorded, or human/computer interactive systems were compared to humans or computers acting alone. Interactive scheduling systems have a variety of forms. They may range, from systems in which humans develop a schedule, to, systems in which the computer decision making has primacy with humans only intervening when corrections and adjustments are required [2]. A common approach is use a computer to build alternative schedules, based on different dispatching rules. These are then compared and a final choice made. Often future outcomes of a schedule may be viewed by using a predictor that steps through forthcoming events. While there is conjecture over some of the findings of these studies, there is general agreement that humans do make use of predictions about future states. There is general concurrence that the maximum number of steps ahead that can be readily assimilated is about three. For a comprehensive discussion of these studies see the excellent and detailed review of the literature by Sanderson [2]. Studies of interactive systems have generally used students and faculty members as subjects. While a few subjects may have some understanding of scheduling, the use of well-formed mental models has not been demonstrated. Mature mental models can only emerge via a process of experiential evolution and testing. This requires long exposure to the scheduling of real systems.
2. MODELLING THE HUMAN SCHEDULER In interactive scheduling, responses coming from the computer have to be in accord with the human's perception of the scheduling process, and consistent with the information-processing capacity and style of the operator. Persons are disinclined to rely on decisions that vary from their own, if they cannot understand the methods and criteria that were in reaching them [3]. An interactive scheduling system also ought to draw on the special competencies humans bring to the scheduling activity. Meeting these criteria depends upon an understanding of how humans approach scheduling. A means for systematically investigating the aspects of system configuration that influence human scheduling abilities and how these aspects exercise their influence led Sanderson and Moray to develop the Model Human Scheduler (MHS) [2]. The MHS, developed from Card's Model Human Processor and Rasmussen's decision ladder, uses as its basic building blocks routines that [4]: 1. recognize system status for current goals,
2. formulate a decision about an appropriate action, and, 3. execute actions to bring the system closer to these goals. The theoretical structure presented in the MHS has been applied by the author to the scheduling of the printing of small batches of forms for computers. A human scheduler developed a schedule by placing cards representing jobs on a board. These were displayed in columns indicating the resource used in their next operation, and were arranged in the order that they were to be loaded. The think-aloud utterances made by the human scheduler were codified through verbal protocol analysis. The data were reduced to production rules in conformity to the MHS framework. A mental model is being developed that depicts the structure of the cognitive activities, rather than finely detailing the actual mental processes engaged by the scheduler [5]. This diverges from the approach taken by Sanderson and Moray, as their interest lies more with the scheduling behaviour at times when pressures affect cognitive processes.
3. THE HYBRID SCHEDULER The model of a human scheduler provides a foundation for the creation of a "hybrid" humancomputer scheduler, where "hybrid" refers to the fusion of human intelligence and machine intelligence [6]. Hybrid scheduling is characterised by: 1. A coherent and active role for humans in the process; 2. Human-computer interaction during the build process; and 3. Cognitive congruence between the methods pursued by the human and the computer. Humans must be actively involved in schedule construction. Only by being alert can they react to critical system events. To keep, or to hone, their skills in information processing, particularly inductive logic and pattern-recognition capabilities, exercise is required [7]. Therefore, the setting and maintenance of a schedule should occupy a significant portion of their attention and abilities [2]. The underlying properties in establishing the schedule should be the subject of examination, rather than mere cursory scanning of the schedule as presented. With the hybrid scheduler, unlike other interactive systems, the human intercedes during the construction of schedules, rather than just responding to choices proposed by the computer. They are able to place the rather diverse set of contingencies that arise into context. The interaction process must be able to cope with the ways that humans address the scheduling problem. While not interfering with the human's `normal' way of thinking, the computer system should extend the human's abilities through the application of suitable abstractions [8]. Underpinning the MHS is Rasmussen's characterisation of three distinct types of problemsolving. They are skill-based (holistic judgment), rule-based (heuristic elimination), and knowledge-based (holistic evaluation) reasoning. A person chooses a particular problemsolving technique for a situation based on experiential familiarity with the task at hand [9]. Alerted to a change in state, the human scheduler may know immediately what action to perform. The computer only needs to be able to present information in its primary form. For example, if the placing of a newly released job in the schedule can be made solely by reference
to the job details (due dates, resource allocations, operations, operation times) and the current schedule. If the circumstances are such that the human scheduler needs to draw upon heuristic rules, the computer system then helps in the choice by applying rules to the primary data. The display then includes the outcomes of different rule choices. The greatest challenge is the making of decisions under circumstances where there are no known heuristics to apply. As humans tend to solve problems in an opportunistic way, this requires tools that allow the human to move to different levels of abstraction in an ad hoc way. For all three decision-making strategies, the computer should be able to help humans go beyond their limitations. For example, to be able to make scheduling decisions in response to rapidly changing events, outcomes, that may occur days or weeks later, may need to be considered. This may be done through simulation. The computer may increase the outlook, beyond the confines of the local group of resources that are being scheduled, to upstream and downstream consequences, through marshalling information from other sources. While humans bring particular insight into the heuristic selection, they may need to be manoeuvred away from their cognitive biases, that could lead to the taking up of an inappropriate strategy. Some biases are, fixation on the first approach to the exclusion of other possibilities, predilection for using easily recalled information, allure of spurious cues, wishful thinking and illusion of correlation [10]. The computer system needs to compensate for these shortcomings. The computer has also to accommodate other human failings. Humans may neither have an upto-date knowledge of system's state, nor an exact mental model of the system's functions and structure. They also suffer from deficiencies associated with time span. The outcomes of their actions may not be understood until a long time later. They find difficulty in determining trends from a set of discrete states spaced widely apart in time. Where components in the system are tightly coupled, they may find difficulty in responding fast enough [2]. Furthermore, persons responsible for scheduling are frequently interrupted by other demands made by the production system. They have to be able to cope with the cognitive discontinuity, on returning to the scheduling task.
4. INTERFACE Several studies have highlighted difficulties with the interface design. Incorporation into the supervisor's internal model an understanding how alphanumeric and graphic information affect them. Poor performance has been observed when graphical displays have been used. The reasons for this are unclear, but some factors that have been surmised. Subjects may believe that they have acquired more information from the displays than what was actually present. They may have difficulty in comparing information that was sometimes graphical and sometimes alphanumeric. 'Visual momentum' may have been lost [2]. Visual display should be seen as critical, as it allows the human scheduler to relate task objects to current information about jobs and machines. The potential of graphical interfaces needs to be carefully considered. Without a thorough knowledge of the quality of the information
display, one is unable to make pronouncements on the quality of the scheduling per se. Sanderson queries the results of studies comparing human schedulers acting alone to their operation with a computerised aid using dispatching rules. She questions whether the results may have been attenuated or even reversed if the interface had been changed [2].
5. THE COGNITIVE WINDOW The format of the display is a salient feature of a hybrid scheduler. Properties have to be displayed in a form that allows for cognitive congruence between the methods pursued by the human and the computer. The syntax of the display must not obscure the data that is being enhanced [10]. Before any schedule is built, the human proposes strategies to which the computer advises on the potential consequences on the production system's performance. These have to be displayed in terms that are relevant and meaningful to the human schedulers. Before expanding upon this, some of the features of early forms of graphical aids for scheduling will be explored. There is long experience in the use of tools for managing the large amount of data needed in the construction of a schedule. The most basic form is a machine planning board, that displays the operations on each resource for every job. A more sophisticated display, a Gantt chart, shows the sequence of operations and the expected utilisation times at each resource, including set-up times. It allows loading times and expected due dates for each operation to be determined. These devices are early forms of interactive systems. They retain information about the jobs and resources using a display that enables a human scheduler to recognize leading features easily. But, they are too cumbersome for rapidly changing environments. An early form of computerised Gantt chart was developed by Shackel to overcome the inability of board-based techniques to respond fast enough to the receipt of new orders that came on average every three minutes [11]. While the Gantt chart is useful for displaying a schedule that has been built, it is unable to assist the schedule building process. During the interactive build of a schedule, the computer display has to reveal the computer's decision-making processes and consequences in terms that are meaningful to the human. Goodstein introduced an integrated display for process control, using arcs on a circle to represent parts of the system. If a malfunction occurs in part of a system, the arc representing that system is lengthened so that the circle becomes deformed. As the malfunction radiates to different parts of the system, the circle changes. If the same problem occurs repeatedly, the operator may learn to make the correct decision based upon the perceptual pattern of the integrated display [10]. Another approach has evolved from ecological psychology [12]. Using the idea of "affordance", graphical techniques are sought that display abstract properties of the internal processes used in building a schedule. Visual cues are presented to the human scheduler help in choosing appropriate strategies that lead to a schedule that meets chosen criteria for good performance of the production system.
6. CONCLUSION In developing a hybrid scheduler, the human's role has to be made coherent and active, and the human and computer approaches to schedule creation have to be in concordance. The underlying decision-making processes that are abstract have to be depicted in a way that corresponds to the human scheduler's mental model. To acquire a solid foundation for hybrid scheduling, answers to the following questions are being sought: 1. What are the scheduling strategies employed by human operators in discrete manufacture? 2. How are these influenced by the abstractions employed in the data presented to the operator about the state of the system and its performance requirements? 3. What are the most appropriate formalisms for representing human decision-making processes in models of discrete-event systems?
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