سیستم مدیریت دانش کامپیوتری برای فرایند استراتژی تولید

This paper presents Co-MASS, a computerized knowledge management system for the collaborative development of manufacturing and operations strategy. The system supports the social and knowledge processes of collaborative strategy development by integrating a domain-specific modelling formalism based on the resource view of the firm, an associated structured dialogue scheme, an argumentation-enabling mechanism, and an efficient algorithm for the evaluation of alternatives. The competence-based manufacturing strategy paradigm behind its design rationale, its main elements, and a use case in a real setting are presented. Evaluation results provided positive feedback for the usability of the system, the discourse structure and the functionality of the user interface. The main contribution of our system lies in the integration of knowledge management, decision support and argumentation features, which constitutes a novel approach to develop manufacturing strategy.

The development of an organisation's strategy, at both corporate and functional level, is a complex and ill-structured task, usually undertaken by a team of managers with diverse backgrounds representing different units [1] and [2]. Independent of the planning horizon and the scope of the final decision, strategy formulation is a knowledge-intensive process that may be reduced to problem resolution, no matter whether it concerns opportunity seizing, goal attainment or defensive moves. Empirical research suggests that to accommodate different views through the process of retrieving, considering and evaluating alternatives, the strategy formulation process moves from a divergence of opinions and views towards their convergence to agreed action items [2]. Obviously, the more different perspectives are initially taken into account, the greater the complexity of convergence, but the smaller the chances of addressing the wrong problem and reaching an inadequate solution [3] and [4]. At the functional level, the manufacturing and operations strategy formulation process has attracted considerable interest over the last 20 years. In this direction, a number of authors, influenced by the application of the “rationalist” paradigm of strategy, have proposed tools and procedures for assessing the manufacturing function's internal and external environment at a particular instance in time, and for identifying the actions needed to achieve fit among them (e.g. [5], [6], [7], [8], [9] and [10]). In all cases, there is the inherent assumption that all manufacturing-related knowledge can be gathered, qualified and codified by a single person, or in a series of facilitated sessions involving manufacturing-language literate managers. In practice, however, the manufacturing function of the modern corporation is closely related to other functions, such as marketing and product development [9], and the overall formulation of its strategy is a slow iterative process, usually requiring the involvement of managers with diverse backgrounds being situated in remote sites, which may even be in different countries [11]. Yet, given the dynamic and unpredictable nature of environmental changes, as well as the dynamic evolution of the related resources, purely rationalistic approaches to manufacturing strategy formulation seem to be insufficient [12]. In practice, it has been noticed that the manufacturing strategy process of successful firms is a mixture of rationalistic analysis and evolutionary sense-making, both becoming effective by an underlying processualist/learning perspective [13] and [14]. This perspective to the manufacturing strategy process entails a different philosophical stance, as far as its design rationale and its leveraging mechanisms are concerned. The design objective is not only how to reach an agreed action plan efficiently, but it is of the same importance to consider the learning that occurs within the process. The latter requires a consideration of the way manufacturing strategists interact during decision making [15]. Towards this end, the intensions and the successful application of various “soft-OR” methods in diverse strategic domains (see, for instance, [16] and [17]) suggest that the collective learning nature of the manufacturing strategy process can be greatly benefited by the collaborative development and manipulation of a structured problem model [18]. The model, whose “formality” may range from a structured problem-specific language to a mathematical formalism, can act as an intermediary or “transitional object” [19] for knowledge elicitation and conversion. To facilitate the collaborative and learning-enhancing manufacturing strategy process in multi-sited enterprises, we have developed collaborative manufacturing strategy system (Co-MASS), a model-driven knowledge management system that relies on internet technologies. Co-MASS supports the social and knowledge processes of the manufacturing strategy development process by integrating a domain-specific modelling formalism based on the resource view of the firm, an associated structured dialogue scheme with an argumentation enabling mechanism, and an efficient algorithm for the evaluation of alternative suggestions/models. The paper presents the manufacturing strategy perspective behind the system's design rationale, its knowledge representation schema and main modules, and a use case from its evaluation in a third-party pharmaceuticals manufacturer.

This paper has presented a web-based knowledge management system for assisting the manufacturing strategy process. Co-MASS aims at aiding a team of managers to reach a decision, not only by efficiently structuring the related discussion on the basis of group dynamics theory, but also by providing an efficient algorithm for the evaluation of alternatives. Our primary goal was to develop an active system that captures the strategists’ rationale and stimulates knowledge elicitation through argumentation on the issues under consideration, while it constantly considers the whole set of the items asserted to update the status of the discourse. Meeting these requirements, Co-MASS not only captures the informal organizational memory embodied in such environments, but also helps the users during the decision making process per se. It should be noted, however, that the proposed system is intended to act as an assistant and advisor, by facilitating communication and recommending solutions, leaving the final decisions and actions to the users. Our future work directions concern the development of a model base, that will integrate alternative modelling formalisms for specific manufacturing strategy issues (e.g. mathematical models for investment appraisal). This will be accompanied by automatically triggered mechanisms to adjust the structure of the discourse graph according to the model used. Future work plans also concern the integration of two additional modules to support simulation and case-based reasoning. The former is envisaged to be used in order to validate the dynamics of a manager's proposal, thus providing additional evidence about the issues considered at each discussion instance [54]. This module could also be used by a manager for testing the impact of his/her assertion on the discourse before inserting it to the knowledge graph. The latter would exploit previous cases, stored in the system's knowledge base, thus increasing the efficiency of the system by enabling managers to consider and reuse instances of similar discussions as warrants to their current argumentation [55].