Project Management PDF

This paper describes how to use Axiomatic Design to create and plan a company-specific strategy. It couuld, for instance, be a technology strategy plan, or a business plan. It is shown that using axiomatic design during the strategic planning process achieves a tight relation between company goals (i.e. functional requirements in the design language), company strategies (i.e. design parameters), and activities (i.e. process variables). When using Axiomatic Design it is possible to do an optimization of the implementation process, i.e. action plan, by solving the mathematical system represented by the design equations. Such an optimization of the action plan minimizes iterations and speeds up the implementation process. Tasks that can be performed independently of other actions are identified and are implemented immediately without considering inputs from other process steps. The approach described is tested and verified in case studies performed within large industrial companies. The results are implemented in industrial practice.

Software development projects require the translation of good abstract ideas into clear design specifications. Subsequent delivery of the software product in moderate-to-large scale projects requires effective project planning and assignments for a team of software engineers to meet deadlines in the presence of resource constraints. This paper explores the hypothesis that axiomatic design may be integrated into the process of project planning and task assignment for software development teams. An approach to mapping functional requirements and design parameters into tasks of a project plan Gantt chart is described. Effects of transferring the relationships of design matrices to task links are discussed. The result is considered by the authors to be a productive integration facilitating the rapid delivery of product by software engineering teams.

The principle of partitioning tasks among product development teams so as to minimize the cost of interactions across design teams is an important characteristic of complex engineered systems. Although there is growing literature that deals with the proper organization of product development tasks, little attention is given to rigorous modeling of the phenomena. To fill the void, we present a mathematical formulation for the problem. Two main issues are addressed by the model: 1) how to specify task dependencies, and 2) how to optimally partition the tasks among a number of teams. In this paper, we suggest to utilize the ‘design matrix’ representation of Axiomatic Design as a means for specifying tasks and their associated attributes. The developed model and solution technique can be applied to various scales of the product design and development process, and may open a variety of interesting questions.

Design process starts with customer needs identification. With companies’ shifting attention from the traditional emphasis on manufacturing capabilities to customer centric, connecting customer into the design process becomes an important issue. This paper presents a systematic approach to connect customers in the product design and development process based on Axiomatic Design. It includes methodologies to capture customer needs, bring different levels of customer needs into the same level of abstraction in the form of product attributes, and prioritize those needs. Customers’ needs can then be mapped into the functional requirements (FR) domain. Based on the proposed approach, manufacturers are able to provide a platform for customers to directly participate in product design and get products that suit their personal preferences, which is termed as Design by Customer. Design by Customer provides not only an effective means to cater to individual customers’ needs but also an avenue to systematically connect customers into the design process.

Mold manufacturing operators have to make a number of decisions for each product. For shortening lead-time of mold manufacturing, we applied axiomatic design, principally the Independence Axiom, to analysis and management of the decisions. At first, we set each human decision as a functional requirement (FR). Our proposed method, a rule of “one decision per one process” or a rule of “no feedback” in a “decision-based process design”, re-scheduled the processes (=DPs) to satisfy the Independence Axiom. For example, among the 583 decisions made for one-mold production, we removed those that the computer could settle, and further reduced the number of selections with the standardization. These improvements dropped the number of human decisions (=FRs) down to the minimum set of 77 independent ones. The less human decisions can reduce the thinking/ negotiating/ waiting time, shortening the lead-time by 14 %.