رویکرد مبتنی بر شبکه پتری برای تجزیه و تحلیل وظیفه ارگونومیک و مدل سازی با تاکید بر انطباق با تغییرات سیستم
|کد مقاله||سال انتشار||مقاله انگلیسی||ترجمه فارسی||تعداد کلمات|
|7226||2003||33 صفحه PDF||سفارش دهید||محاسبه نشده|
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Safety Science, Volume 41, Issue 10, December 2003, Pages 803–835
Task analysis has been extensively used in industrial ergonomics in order to identify system demands and operator plans for achieving goals and coping with high workload. On the other hand, computer modeling has been used for simulating human–machine interactions under a range of conditions, such as changes in task allocation, team structure, operating procedures and system events. To integrate task analysis and computer modeling, a new technique is proposed that utilizes Coloured Petri Nets. The proposed technique has been developed on the basis of 12 requirements reflecting aspects of task representation, control and decision making, and usability. A Petri Net notation of tasks and a classification of Petri Net-based plans are first introduced. This article is mainly concerned with the development of routines for making task sequences and plans adaptable to system changes that could give rise to task interruptions, changes in goal priorities, changes in task allocation, high workload and human errors. An evaluation follows on the basis of the specified requirements for task analysis and task modeling. Relevance for the industry: Task analysis and task modeling are important for matching systems demands to operator capabilities. New computer modeling approaches, including Petri Nets, can simulate human–machine interactions under a range of conditions, such as technology innovations, changes in team structure, different allocation of tasks, and high workload.
Modern work systems require reliable human interventions, efficient team cooperation and adaptation to changes caused by technological innovations or unforeseen events. To achieve these work requirements, a range of task analysis techniques have been developed in the domain of industrial ergonomics (Kirwan and Ainsworth, 1992; Luczak, 1997 and Schraaggen, 2000). Task analysis involves the study of activities and communications undertaken by operators and their teams in order to achieve a system goal. The task analysis process usually involves three phases: (i) collection of data about human interventions and system demands, (ii) representation of those data in a comprehensible format or graph, and (iii) comparison between system demands and operator capabilities. The primary objective of task analysis is to ensure compatibility between system demands and operator capabilities, and if necessary, to alter those demands so that the task is adapted to the person. Kirwan and Ainsworth (1992) summarized several techniques developed for each phase of the task analysis process. Verbal protocols, questionnaires, and activity sampling are examples of techniques for task data collection while flow diagrams, timelines and hierarchical task analysis are helpful for describing operator’s activities and plans. On the other hand, computer modeling and simulation techniques (e.g. Micro SAINT) have been developed to simulate the task and evaluate human–machine interactions under a range of conditions. Here different task configurations, team structures, operating procedures and monitoring strategies could be evaluated. Nowadays, advances in information technology and computer modeling would allow the development of task analysis techniques that achieve both phases of task description and task simulation within the same framework. This is a challenging research issue because, on several occasions, the requirements of task analysis and simulation may be conflicting. Task analysis, for instance, requires descriptions that are easily understood by different specialists (i.e. designers, users and computer experts) while task simulation requires a formal language of specification. In task analysis, we can use abstract descriptions of human activities in cases where we want to allow for some flexibility in the way that tasks are performed, or where we don’t know at a certain stage the optimal sequence of activities. This kind of ‘temporal abstraction’ (Killich et al., 1999) is difficult to find in task simulation and computer modeling since these require precise specification of the flow of activities. There are also different perspectives taken by these two approaches, such as the task analysis focusing on the flexibility and reliability demonstrated by human operators and the task simulation focusing on precise specification and verification of human activities. In this sense, the purpose of this article is to present a new approach for integrating task analysis and computer modeling of performance within a single framework. Existing approaches to the integration of task analysis and simulation, such as Micro SAINT and WinCrew (Laughery and Corker, 1997) and HOS (Glenn et al., 1992), have provided useful insights. The proposed approach is based on a Petri Net representation of human activities, tools, and organizational roles. Petri Nets are cast both in a graphical form and a mathematical formalism. Although most of the modeling work can be done with the Petri Net graph, the mathematical foundation provides the basis for using a variety of formal analysis techniques that can be built into software packages to examine the structural and dynamic properties of Petri Nets. It is possible to examine, for instance, whether the task network contains deadlocks, never-ending tasks, ‘dangling’ tasks that do not contribute anything, and tasks that are activated unintentionally resulting in lack of synchronization. These properties of liveness, boundness and fairness can only be investigated with formal analysis techniques, such as reachability graphs, place invariants, and reduction rules. There have been very few applications of Petri Nets to ergonomic task analysis and modeling. Oberquelle (1987) was among the first researchers who used a general net approach (i.e. Roles, Functions and Action, RFA nets) to task analysis but has not specified a formal notation for the RFA nets. The work of Coovert and his colleagues (Coovert & Craiger, 1997, Coovert & Dorsey, 1994 and Coovert & McNelis, 1992) is notable for applying traditional Petri Nets to the analysis and training of tasks. In the context of human error and accidents, traditional Petri Nets have been used in the modeling of accident sequences (e.g. Love & Johnson, 1997, Johnson, 1998 and Kontogiannis et al., 2000). More recent studies have focused on Coloured Petri Nets that model the flow of coloured tokens or ‘data structures’ throughout the task network instead of the flow of single values. The work of Levis and his colleagues (Shin & Levis, 1999, Weingaertner & Levis, 1989 and Wagenhals et al., 1998) is an example of Petri Net models of command and decision making in military tasks. On the other hand, there has been a growing interest in workflow management systems that utilize Petri Nets (e.g. van der Aalst, 1998a and Salimifard & Wright, 2001a). It is conceivable that similar modeling concepts and techniques can also be developed for ergonomic task analysis and modeling, an effort undertaken in the current work. Coloured Petri Nets (Jensen, 1997a and Jensen, 1997b) have been chosen as a candidate for task analysis and modeling because they provide facilities for hierarchical and timed descriptions, communication of ‘data structures’ (i.e. coloured tokens), simulation of tasks, and formal analysis in terms of reachability or occurrence graphs. Task analysis can be carried out by decomposing tasks into hierarchies of operations and plans in a manner similar to hierarchical task analysis (Shepherd, 1995). For this reason, a classification of plans has been developed for Petri Net-based descriptions of human plans and task sequences. Structural and dynamic properties of the task network are investigated with the use of occurrence graphs that are automatically constructed by the Design/CPN software package. The simulation facility of Design/CPN is used for collecting performance data, such as time to perform tasks, idle time for operators and machines, product throughput, and operator workload. In addition, task simulation allows analysts to explore a variety of questions related to aspects of plan implementation. Some of those questions include the following: Are there enough resources (human operators and tools) to achieve a plan? How long will it take to achieve a plan? Are there any periods where some operators are overloaded or waiting idle? What deadlocks should be avoided to ensure that the goal is achieved? What activities should be done in parallel to speed-up a task without creating deadlocks? These questions have guided the current work in modeling task activities with Petri Nets. This article is organized as follows. The second section presents some requirements for task analysis and task modeling that have been used to develop and evaluate the proposed Petri Nets-based technique. The third section contains a short introduction to traditional Petri Nets while the fourth section presents a Petri Net-based description of a taxonomy of plans. The fifth section raises a number of issues regarding adaptation of task modeling to system changes. The sixth section presents a generic description of tasks in terms of Coloured Petri Nets and introduces several programming routines for exploring aspects of operator workload and for making task networks adaptive to system changes and human errors. Finally, a case study is presented for illustrating the types of workload data that can be collected while an evaluation of the proposed technique is finally made in the concluding section.
نتیجه گیری انگلیسی
The proposed technique was aimed at integrating both task analysis and task modeling within a single framework. The 12 requirements have been derived from the existing literature in order to provide a basis for developing and evaluating the new technique. The requirements of adaptation to system changes, task simulation and formal analysis have been proposed by the author to allow for task modeling and simulation. The requirement of state-based and event-based descriptions supplements the eight requirements suggested by Killich et al. (1999). Three main contributions have been made in the current work. The first one concerns the development of a classification scheme of plans to facilitate learning of Petri Net-based descriptions, transfer of expertise from manual methods of task analysis and identification of different control sequences and task demands (e.g. time sharing of activities). The second contribution concerns the development of a Petri Net notation of task structures as illustrated in the job assignment process of Fig. 4. The final and main contribution regards the writing of routines in Standard ML for achieving an adaptation of task sequences to system changes that could give rise to task interruptions, changes in goal priorities, changes in task allocation, high workload and human errors. A concise evaluation of the technique can be made in terms of the twelve requirements presented in Section 2. Other studies utilizing Petri Nets in workflow management systems are also cited here in order to provide support for some merits of the proposed approach that, although within its reach, have not been demonstrated in this article. The proposed technique presents an integrated view of control and information flows, but not of object flows. Attributes of objects could be modeled in the task tokens but the movement of objects (e.g. documents, equipment, and catalogues) would require other techniques such as the Role Function Action (RFA) nets proposed by Oberquelle (1987). Representation of physical tools and organisational roles can also be modeled as attributes of task tokens. A good example of another approach has been the work of Salimifard & Wright, 2001a and Salimifard & Wright, 2001b in the context of workflow management systems. However, the strict specification of organizational roles suggested by Killich et al. (1999)—where the whole task or work organization is modeled in terms of roles—has not been achieved here. The Role Function Action nets (Oberquelle, 1987) satisfy fully this requirement but possibly this is not necessary in the manufacturing and process control industries. Instead, the requirement of state-based and event-based descriptions is more important for those industries. State-based descriptions are at the heart of Petri Nets and provide a convenient way for modeling data-driven aspects of the task. This requirement is fully satisfied by the new technique. The current work has focused mainly on aspects of control, command and decision making. In this sense, the proposed classification of plans seems to be valuable in achieving several requirements of task analysis. The plan taxonomy has been the result of an integration of hierarchical task analysis (Kontogiannis and Shepherd, 1999) and workflow patters (van der Aalst et al., 2000). It may be argued that a hierarchical task analysis can easily be transformed into a Petri Net with the use of the plan taxonomy. To a certain extent, the plan taxonomy can accommodate some aspects of temporal specification of the flow of activities. The discretionary plans, the unordered sequence, the deferred choice and the probabilistic choice plans allow for more abstract descriptions of activities. In this sense, several aspects of this requirement can be fulfilled with the taxonomy of plans. It is very difficult to satisfy completely this requirement because Petri Nets have a formal notation requiring high precision in specifying how a task is performed in a network. Adaptation to system changes has been satisfied in many respects by the new technique. At least, the basic architecture for introducing some types of adaptation has been presented here. The new technique can accommodate adaptations of task sequences to system demands, such as switching between parallel and serial processing, changing the allocation of tasks to personnel, changing the priorities of goals and tasks, interrupting tasks and resuming tasks. In addition, workload and human errors can also be modeled in order to collect performance data or explore their effects on the task structure. It is desirable that more sophisticated models of workload and human error are developed in future. The requirement of cooperation and decision making has not been explored adequately in this article. Other studies in the context of workflow management (van der Aalst, 2000) and command and control military systems (Shin and Levis, 1999) have shown that Petri Net-based descriptions of collective tasks have been very useful in identifying points of lack of synchronization. The new technique does not show explicitly interactions between team members since these are not made visible in the Petri Net graph. This weakness was a side effect of the adaptability in the allocation of tasks when high workload and errors occurred. Further research is needed to explore how we can achieve adaptability by depicting team members and communications on the Petri Net graph rather than hiding them inside the code segments. The requirement of decision making has been partially satisfied. The taxonomy of plans makes an important distinction between explicit and deferred choices while several types of control sequences are illustrated. However, many aspects of decision making have not been made visible in the Petri Net graph because they were incorporated in the code segments. In general, a representation of dynamic decision making may clutter the graph with too many arcs. On the other hand, reliance on code segments would reduce visibility of decisions on the net. There are very few studies that have developed flexible and dynamic models of decision making based on Petri Nets (e.g. Shin & Levis, 1999 and Wagenhals et al., 1998). This area needs further developments by Petri Net researchers. The utility driven requirements have been satisfied to a large extent; this argument is in agreement with the Killich et al study. The new technique presents a hierarchical view of task description whereby complex tasks are replaced by nested hierarchies. However, the descriptions are not truly hierarchical in the sense that Lakos (1997) argues. It is not possible, for instance, to have ‘abstract’ task tokens at the different levels of the hierarchy that change their structure as they move between levels. Lakos (1997) presented an intriguing architecture for achieving this sort of flexibility in task tokens. The requirements of transparency and usability, on the other hand, have been satisfied to a certain extent. However, some knowledge of Standard ML is needed in order to specify the code segments and use the existing routines proposed in this article. Finally, the requirements of task simulation and formal analysis have been fully met by the notation of Petri Nets. Overall, the new technique demonstrates that task analysis and task modeling can be integrated in a single framework. Several aspects of adaptability have been explored and implemented although, in some cases, it was not possible to show the demonstrated adaptability on the Petri Net graph. New work has already started in exploring how to achieve this sort of adaptability on the Petri Net graph rather than on the code segments. Research in Petri Nets is growing and the results seem to be applicable to ergonomic task analysis and modeling. Especially, developments in object-oriented Petri Nets are very promising for incorporating aspects of inheritance of task attributes and evolutionary changes in work design (e.g. Van der Aalst & Jablonski, 2000 and Lakos, 1995).