Standards, codes, and specifications play an important role in the design of buildings, bridges, and other engineering systems. A design configuration must be checked against all standards to ensure that it is acceptable. This process of design conformance checking using standards is often very tedious. The successful automation of conformance checking is one of the components of a comprehensive computer-aided design system. In that past, standards were interpreted and converted into application programs written in procedural programming languages such as FORTRAN. This approach is extremely inflexible and often error-prone. To support a fully automated computer-aided design system, standards must be incorporated into the design process in a more generic and flexible manner. This paper investigates the feasibility of alternatively casting standards in a form suitable for processing in a knowledge-based expert system environment. The emergence of expert systems from artificial intelligence research has provided a technology that readily lends itself to the automation of design standards. Knowledge-based expert systems have become a powerful tool in tackling domains like design where some of the problem-solving knowledge is diverse and ill-structured. Using an expert system tool, a standard can be represented and processed independent of a CAD application program. Two prototype standards processing systems utilizing the production system approach have been constructed and are presented herein. Although the obvious direct translation casting the provisions of a standard as rules in a production system has its advantages, a more generic and flexible representation scheme is proposed herein. The approach advocated in this paper is to represent standards as databases of facts which can be readily and generically processed by an expert system. The database representation is derived from a unified view of standards obtained by using the standards modelling tools proposed by previous researchers in this field during the past decade. Building on this existing technology resulted in a knowledge- based standards processing architecture which is generic, modular, and flexible. An implementation of this architecture is presented and describe