Concept Synthesis PDF

This paper is an extension to the formulation presented in Part I and deals with design situations where there is no sufficient information to warrant the use of Part I deterministic optimization. The formulation assumes the existence of a design alternatives pool with enough expertise to score ranking against the selected criteria. Part II builds upon the rationale adopted in Part I for the selection criteria and the integer programming. Therefore, a function of complexity, value, cost and customer satisfaction will be used as an objective function criterion. This rationale is rooted in the concepts of QFD, axiomatic design and value engineering. The formulation is expanded to include technical and assembly feasibility as constraints. The formulation uses some concepts of fuzzy set theory to quantify complexity, a formulation ingredient.

The motto of the World Confederation of Productivity Science “Wealth, Prosperity and Peace through Productivity” is an important true statement that is important fully to understand. However, it is also an important imperative to everybody in politics, civil services as well as in industry. Especially in manufacturing industries which have a direct effect on the wealth production, as it creates the tools we need in our daily life, this imperative is evident and very important. Studies have also shown a direct correlation between investment level in a country and the increase in labor productivity. Wealth production also requires that we create and produce the products that are needed in order to improve the welfare. We understand this as quality, “fitness for use”. Today many products are complex systems that have to be designed in order to meet specific customer requirements on functionality, reliability and easy use. Market timing is also very important in order to meet the market windows, which especially for IT products are very short in time. Complexity must be combined with understandability and easy use through skillful engineering. Success requires today that the production processes and systems are designed integrated with the product design. We understand this as concurrent engineering. In order to improve our skill in engineering design we have to understand the fundamental principles of good design and define and use a decision theory for development work. Such a theory can be defined with Axiomatic Design as a base. This can be further developed, taught and used in practice in order to improve productivity and quality in industrial product realization. We have also to distinguish between tools, methods and fundamental principles for engineering design. Products and processes also steadily include more knowledge through the use of information technology. The use of modeling techniques and information technology integrated with such a decision theory is important.

The concept selection problem is to select the ‘best’ conceptual design solution entity from a pool of feasible alternatives in the early concept design stage. The determination of a good selection criteria is a key for successful design release. In this paper, the concept selection problem is formulated as an integer programming problem. Complexity, value, cost and customer satisfaction are used to derive the objective function criterion. The mathematical form of the proposed criterion can be conveniently obtained by borrowing from the concepts of QFD, axiomatic design and value engineering. The criterion is then employed into our integer programming formulation which is expanded to include technical feasibility and assembly feasibility as constraints. The proposed formulation is sufficiently robust to adapt design situations with deterministic information (Part I) or fuzzy information (Part II).

International Conference “MECHANIKA 2001”. Kaunas, Lithuania. April, 2001.
The field of design, be it dedicated to products, processes or organizations, has undergone and is still undergoing an intellectual renaissance – from the still prevailing notion that design can be learned only from experience, to the idea that it may be amenable to a systematic and scientific treatment. Although these design activities in different fields seem to be distinct, cognitive processes and design principles are used in all fields, thus existing many ways to approach it. The axiomatic approach is one of them, and it gives a general theoretical structure, common to all fields. In the product development process adopted, the design activity is defined as having four phases: informational, conceptual, embodiment and detailed design. Among them, the two earliest phases are detached, where the decision taken has a broaden effect on the product’s success or failure. In this sense, as an aid to the development of these two design phases, is been developed at the Group of Integrated Product Development at the Federal University of Santa Catarina (Brazil), researches aiming to determine methods and tools to aid the product development. The overall goal of this work is to study the axiomatic approach to design with emphasis on the decision-making process and to contribute to the product conceptual design informatization, registering the relations between functions and solutions. Through the identification of these relations it is intended to reduce the function-solution dependence. The greater the independence, the better the project, according to the axiomatic approach. Therefore, the research to be performed aims to determine how the axiomatic approach and its computational implementation may contribute to the product conceptual design phase.

MIT Department of Mechanical Engineering, MIT, Cambridge, MA, September, 2006.
To efficiently design safety-critical systems such as nuclear power plants, with the requirement of high reliability, methodologies allowing for rigorous interactions between the synthesis and analysis processes have been proposed. This paper attempts to develop a reliability-centered design framework through an interactive process between Axiomatic Design (AD) and Fault Tree Analysis (FTA). Integrating AD and FTA into a single framework appears to be a viable solution, as they compliment each other with their unique advantages. AD provides a systematic synthesis tool while FTA is commonly used as a safety analysis tool. These methodologies build a design process that is less subjective, and they enable designers to develop insights that lead to solutions with improved reliability. Due to the nature of the two methodologies, the information involved in each process is complementary: a success tree versus a fault tree. Thus, at each step a system using AD is synthesized, and its reliability is then quantified using the FT derived from the AD synthesis process. The converted FT provides an opportunity to examine the completeness of the outcome from the synthesis process. This study presents an example of the design of a Containment Heat Removal System (CHRS). A case study illustrates the process of designing the CHRS with an interactive design framework focusing on the conversion of the AD process to FTA.