This concept note has been prepared for the automobile manufacturing companies stressing the importance of employing Knowledge-Based Engineering systems with the aim of improving their fields of developmental methodologies through a shorter developmental time thus improving the quality of their systems(ARMSTRONG, 2001:24).
Analysis of the Context
The concept of Knowledge-Based Engineering(KBE) is without a doubt very broad. This is because in product development KBE becomes an important tool with the important function of capturing knowledge and enabling for its reuse. For example, a spreadsheet enables the recycling of knowledge by having the ability to effectively implement equations and/or rules. It is for this reason that this concept note lays emphasis on those tools of Knowledge-Based Engineering that function as tools where knowledge is stored in different classes as objects such as Java, C++ and especially takes note of fact that in terms of product prototyping, KBE tools carry out an important role in congruence with geometry engine to effectively put into action the automatic generation of product concept.KBE functions to automate routine and time-consuming tasks which thereby accord employees of companies more time to invest in new innovations and adequately find solutions. However, a knowledge-based system emanating from artificial intelligence(AI) captures expert knowledge and more often than not also generates creative solutions, for which it sometimes referred to as an ‘expert system’.This paper notes that in the development of KBE systems,numerous methods exists but lays particular emphasis on MOKA as a suitable example that could be adopted by SMMT (The Society of Motor Manufacturers and Traders), as the development process revolves around capturing and formalizing knowledge which does not present challenging difficulties to most manufacturers(HIRZ, 2013:309).
KBE will offer automobile manufacturers the advantage of optimizing product concepts in a much easier way and even importantly guarantee that the process knowledge is therefore stored. However, the disadvantage is that it demands a lot of time to develop the systems.