Modelling Human Aspects of Collaborative Scheduling

Journal of Advanced Computational …, 2006

The model we present supporting collaborative scheduling in complex dynamic manufacturing envi-ronments, considers the interaction between an agent-based scheduling module (ASM) and a group decision support module (GDSM). The ASM outputs a set of candidate ...

Activities involving more than a single participant need to be coordinated. This requires multiple parties schedule their joint activities together. Multi-party scheduling consists of the development and maintenance of schedules of activities across organisational groups. Where uncertainty, ill-defined information and changing situation are involved, human cooperation is vital in making decisions. When cooperating, schedulers view a range of tasks, plans and resources as common. However, their domain knowledge differs and they have individual goals and tasks. Hence, cooperative and individual activities must be harmonised, in a holistic framework of true collaborative state. This paper presents a cognitive analysis of the cooperative activities as schedulers coordinate joint tasks. It sets a foundation for studying the cognitive behaviour of schedulers when cooperating. A model of Cognitive Work Analysis for decision-making with multiple goals is applied and extended to include interactions between collaborators. The interactions are cooperative activities, where cooperation is viewed as a process of interference management.

Inter-organizational scheduling is a process, where two or more organizations coordinate activities for mutual benefits. Decision making in such an environment is a multi-criteria, multi-party practice, including cooperation between parties. It is characterized by distributed, dynamic, ill-defined and conflicting information. As this information is in the form of tacit knowledge, its efficient transference between organizations is not possible through databases and computer-supported tools. Therefore human collective work remains a key factor in interorganizational scheduling. This, comprising interaction between human operators, algorithms, software, and autonomous agents implies a need for structural and functional concepts. In this paper, inter-organizational dynamic collective work is studied using a cognitive-based analysis. Our aim is to identify the key factors affecting the process. Through a comparative review of the literature, it is argued that cooperative processes, involving coordination mechanisms, are one component of collaborative states in collective works in scheduling between organizations. In such a way, in collaborative scheduling, group and domain knowledge and tasks, group knowledge, group decision processes, and cooperative activities play a key role. This approach can contribute in system analysis, (re) design, and evaluation as well as designing computer supports in inter-organizational scheduling.

2000

Activities involving multiple participants need to be coordinated. It requires parties schedule joint activities together. Multi-party scheduling consists of the development of schedules across organisational groups. Where uncertainty and ill-defined information are involved, human cooperation is vital in making decisions. Schedulers view a range of tasks and plans as common. However, their domain knowledge differs and they have individual goals

Establishing the Foundation of Collaborative Networks, 2007

Scheduling is a multi-criteria decision problem in practice, where different schedulers may agree on key objectives but diller greatly on their relative importance in a particular situation. This kind of"problems can be tackled with Collaborative approaches, which is the aim of" this work. Collaboration supports work being undertaken bv dispersed entities allowing the sharing of" final results and also the process of" obtaining them. This involve a range of" activities such as inf"ormation exchanging, knowledge sharing, argumentation, problem solving strategies, role playing, group mediation, individual training and conflict resolution, among other. Here, we propose a Collaborative fi"amework with an Adaptive behmJiour to be used in Manuf"acturing Scheduling Environments. 1 INTRODUCTION Today organizations pursue the global objectives of high resource utilization, fast order turnaround and outstanding costumer service. The latter relies on delivery accuracy, i.e., delivering goods on time, with quality and low costs. These are some critical factors of success of an organization, so one of the main aspects for competitiveness and success of an organization is the efficient production managing, particularly in production scheduling which is a complex problem when dealing with multiple criteria sometimes with conflicting goals in dynamic environments with high degree variation factors. This scenario is more problematic because it is known that in reality variables behaviour is not the same as planned, so there is a strong possibility to reformulate the existing plan and the need to change current schedule to adapt to emerging modifications. Generally, we may say that the present business environment is characterized by the use of groups, working in distributed environments and dealing with uncertainty, ambiguous problem definitions, and rapidly changing information. Scheduling decisions are often characterized by goals, roles, activities and resources that are dynamically changing, or uncertain. For improved competitiveness scheduling decisions should arise from the integration of different production functions where each participating actor collaborates in achieving a solution. The purpose of this work is to develop an Adaptive Collaborative Framework that uses Group Decision Support (GDS) and Adaptation concepts to support the scheduling process on manufacturing environments. This paper is organized as follows. Sections 2 presents a background research giving a general approach to Collaborative Scheduling, Group Decision Support and Adaptive Systems. The architecture and interaction model to support Adaptive Decision Support in Collaborative Scheduling are presented in section 3, and an

IFIP International Federation for Information Processing, 2006

The scheduling process, usually involve the evaluation and selection of one alternative between a set of them. These decisions are not trivial, considering that they usually involve multiple, and sometimes conflicting, criteria. Particularly in scheduling which aim is to find the trade off between loading efficiency and delivery accuracy taking into account holding costs, tardiness penalties and expedition charges. Scheduling decisions should be taken in respect with the result of the integration of different criteria weighted according the several perspectives from manufacturing environment nameky, production, commercial, and quality. So, scheduling is a multi-criteria decision problem; in practice different schedulers may agree as to the key objectives but differ greatly as to their relative importance in any given situation. The purpose of this paper is to address collaborative scheduling in complex dynamic manufacturing environment, presenting a collaborative scheduling approach which considers group decision support.

We studied the process of production scheduling in a large chemical plant. Scheduling in that environment is inherently a group process because multiple experts are needed to construct a schedule and to manage its execution. A mathematical formulation of the production scheduling problem yields a mixed-integer linear programming model too large to solve in a reasonable time with current technology. We therefore use an intelligent decision support system (DSS) to heuristically find a satisficing solution to the production scheduling problem. Our DSS is based on a model of the collaborative nature of the task, and it focuses on the communication, argumentation, and reconciliation strategies undertaken by individuals. Using actual production schedules, we show that our DSS can lead to measurable improvements over humanly-designed plans, where the quality of the schedule is measured using the objective function of the mathematical formulation of the problem.

This paper is concerned with the design of distributed decision support systems for organizations (companies, project consortiums, virtual enterprises), in which several decisionmakers have to cooperate. Typical situations can be found in the domain of the distributed management of time and resources (i.e. planning, scheduling, personal management, allocation of shared resources...). Each decision-maker has some latitude that enables to accommodate himself with unpredictable changes of his environment without disturbing the overall organization, making this last more reactive. Nevertheless this autonomy must be evaluated and controlled to ensure the global consistency of local decisions. To facilitate autonomy regulations between decision-makers, we propose to design tools supporting both local problem solving and cooperation. Our approach is based on a rigorous but non-deterministic use of CSP models and constraint propagation mechanisms ([16]). The goal is the improvement of the r...

The hierarchical production planning and control has been disputed since the early 1990s and a paradigm shift has emerged that highlights the role of humans in controlling job shops. However, most approaches to supply chain management still follow the conventional hierarchical approach, which establishes the interaction between supply partners at the management control level and does not consider decisional role for shopfloor control level.

Studies in Informatics and Control, 2011

The work presented in this paper highlights how a real scheduling problem can be considered as a process avoiding the traditional operation research-based approach. Understanding the scheduling problem as a dynamic, uncertain and continuous process, in order to reduce the gap between reality and academic models, new conceptual elements emerge. The framework includes methodologies, concepts, architecture, and algorithms, which are based on the idea of a multiagent system in which planning-scheduling relationship is the core proposal. From the framework a software platform has been developed and tested in real industry.