How do knowledge systems support new product development?
Much has been written about knowledge-based engineering (KBE) systems and the role they play in new product development. Some speculate that these systems only automate the task of creating product iterations by using a rule-based repository as a starting point versus a blank sheet of paper. Rather than promoting innovation, they force design engineers into using existing data and don't allow for the freedom of creative thinking. Others state that these systems propagate innovation by automating routine work that goes into design engineering and engineering process management, therefore allowing more time for creative work, which is the fuel of innovation. To maximize the benefit of this automation, the knowledge rules have to be closely embedded into the product development system. Stand-alone KBE solutions restrict the ability to adapt designs while ensuring adherence to product rules. Taking this approach, companies can devote more time to identifying real market problems, or requirements, and more time to looking at alternative solutions—both fundamental activities in product innovation.
By capturing and automating product engineering and process standards, KBE systems automate the achievement of lower-difficulty product goals and ensure that the content of the product that embodies known concepts is developed extremely efficiently. Development teams can then apply more of their energies to higher-difficulty product functional and requirements analysis, value identification, and breakthrough product scenarios.
What is the benefit of embedding knowledge-based tools within the design solution?
Embedding knowledge-based tools within the design solution allows companies to capture both tacit and explicit knowledge for reuse, but does not restrict the designer from experimenting and attempting "what-if" investigations. Allowing the combination of rules-driven design with traditional design tools enables designers to generate the core design based upon known best practices then add custom design elements and use the rule base to verify conditions such as manufacturability or fitness for purpose.
Can you provide an example?
A typical example of this can be found in the area of machinery design, where it is common to use processes such as configure-to-order or engineer-to-order. Companies often find that 75 percent of the requirements can be met with a standard modular design. Using knowledge-driven tools to generate the correct configuration, designers can complete the design, allowing for a mix of innovation while reaping the benefits of design reuse.
How do rules-based solutions support industry best practices?
Rules-based solutions can ensure that industry best practices can be embedded (i.e., for mold design), reusing standard parts and allowing confidence in design. However, embedding them within the design solution ensures that the designer has a wide range of tools available to enhance the design and enable the creation of variations that potentially improve efficiency and deliver innovations.
Reach Brown at firstname.lastname@example.org.