Last Updated: 2-2018
The rising complexity of demand specifications formulated by unprofessional clients within the AEC-industry induces Designers and Engineers (D&E) to adjust their strategies in regards to Design Management (DM). Inexperienced clients are often not technically skilled. This makes it very hard to capture the right interpretation of the client’s intentions for a specific requirement by D&E prior to the formulation of product specifications that satisfy the demand. This research focuses on the translation procedures of quantitative and qualitative client specific requirements into product specifications for conceptual design stages. The objective of this research initiative is to explore the possibilities to introduce automation as a technique to optimize these reoccurring translation procedures in regards to effectiveness and efficiency.
Within this research, a literature study was conducted on the topics of the design process, Systems engineering, Knowledge Management and Natural Language Constraints. The findings from the review of literature were merged with the observations obtained from interviews held with specialists from the field of Systems Engineering. Based on the findings from these methods, a methodology has been developed. This method has been accommodated by means of an evolutionary prototyping process within a software program, named as ‘The Bank of Knowledge’. This program, on the one hand, accommodates a method that can translate both quantitative and qualitative client requirements into product specifications by means of automation. On the other hand, this program provides a digital environment in which words that are extracted from client requirements can be stored in a structured way within databases for future use.
This research concludes that the eventual way of designing a more advanced and intelligent automated translation system is heavily depending on input such as: the formal language in which requirements are specified, the standardization of concepts in a domain specific language, and databases in which information and data in regards to client specific requirements has been captured. This research also contributed by concluding a set of preconditions for the automation of a more advanced and intelligent system: the operational functions such as Create, Read, Update and Delete (CRUD) need to be accommodated, the system needs to automatically store enriched words by means of a formal notation and standardized concepts, the system is required to automatically equate and allocate the enriched words on a system level, the system needs to automatically capture and distinguish definitions of the obtained words in relation to acting disciplines in order to formulate a product specification, the system needs to run on databases that contain valid knowledge obtained from a variety of projects as delivered in the past.