- مبلغ: ۸۶,۰۰۰ تومان
- مبلغ: ۹۱,۰۰۰ تومان
Efficient multiple project management is very important to the project-based industries. Current multi-project studies in shipbuilding focus on designing mathematical models and heuristic algorithms to achieve optimal resource usage. However, due to the rigid requirements on complete information, these models are inapt to support decisions in the early stages (such as the project biding stage) that have been acknowledged more and more critical in the ever fierce market. On the other hand, although pieces of information management software have been developed for project management and production, there are works left to be manually executed, such as production prediction of a new project and control of the temporary system access delegated to business partners, hindering further improvements in work efficiency. To bridge these gaps, this paper innovatively proposes a governance platform architecture based on the theory of Governance of Projects. The framework views organization management as important as project management and adopts a new access control method which helps reduce the manual labor. Moreover, a case-based reasoning algorithm that supports planning prediction with limited information is designed. Finally, a prototype system is developed and tested in a shipyard in China. It proves to be both effective and efficient.
Effective multiple project management is a vital issue to shipbuilding companies. The information management systems built so far are inapt in this context because of limitations in the underlying theory and some missing functions. Governance of Projects (GoP) is an advanced multi-project management theory that controls either multiple organizations or multiple projects. Thus, this paper tried to develop a GoP platform for shipbuilding companies to manage multi-projects with as little as possible manual work. Particularly, three concrete goals, namely a framework to utilize existing information management software as a whole, automatic information access assignment and the production prediction of a potential project were achieved by the proposed platform. The proposed methods and the developed prototype system add both academic and application value to this study. However, this research also has limitations. Firstly, it is limited to shipbuilding companies in China which are subjected to inconsistent computer aids for multi-project management. Applications in other industries are certainly required to test the effectiveness and efficiency of this work. Besides, more attention is required on the middleware selection to integrate the four conceptual layers. For efficiency and accuracy improvements, the proposed CBR-based algorithm needs further revision, especially when there is a large number of projects in the case base. In this regard, how to make full use of the project cluster to reduce the search space is a direction. The present project cluster method is merely based on the product, so more cluster criterion could be designed and tested for improvements. Another weakness is that PBO reasoning in the GoP platform now can only deal with clear and simple organization relationships. Judging from the evaluation section, it can be seen that the total false rate reaches 14% in one design process. So, special design of more complex inference rules and development of a more strong inference engine is worthy of research efforts. Considerations should also be taken into the way to employ more GoP mechanisms in the GoP platform.