Knowledge-based configuration, also referred to as product configuration or product customization, is an activity of customising a product to meet the needs of a particular customer. The product in question may consist of mechanical parts, services, and software. Knowledge-based configuration is a major application area for

artificial intelligence Artificial intelligence (AI) is the capability of computer, computational systems to perform tasks typically associated with human intelligence, such as learning, reasoning, problem-solving, perception, and decision-making. It is a field of re ...

(AI), and it is based on modelling of the configurations in a manner that allows the utilisation of AI techniques for searching for a valid configuration to meet the needs of a particular customer.

Background

Knowledge-based configuration (of complex products and services) has a long history as an

application area, see, e.g. Informally, configuration can be defined as a "special case of design activity, where the artifact being configured is assembled from instances of a fixed set of well-defined component types which can be composed conforming to a set of constraints". Such constraints represent technical restrictions, restrictions related to economic aspects, and conditions related to production processes. The result of a configuration process is a product configuration (concrete configuration), i.e., a list of instances and in some cases also connections between these instances. Examples of such configurations are computers to be delivered or financial service portfolio offers (e.g., a combination of loan and corresponding risk insurance).

Theory and complexity of configuration

Numerous practical configuration problems can be analyzed by the theoretical framework of Najmann and Stein, an early axiomatic approach that does not presuppose any particular

knowledge representation Knowledge representation (KR) aims to model information in a structured manner to formally represent it as knowledge in knowledge-based systems whereas knowledge representation and reasoning (KRR, KR&R, or KR²) also aims to understand, reason, and ...

formalism. One important result of this methodology is that typical optimization problems (e.g. finding a cost-minimal configuration) are

NP-complete In computational complexity theory, NP-complete problems are the hardest of the problems to which ''solutions'' can be verified ''quickly''. Somewhat more precisely, a problem is NP-complete when: # It is a decision problem, meaning that for any ...

. Thus they require (potentially) excessive computation time, making

heuristic A heuristic or heuristic technique (''problem solving'', '' mental shortcut'', ''rule of thumb'') is any approach to problem solving that employs a pragmatic method that is not fully optimized, perfected, or rationalized, but is nevertheless ...

configuration algorithms the preferred choice for complex artifacts (products, services).

Configuration systems

Configuration systems, also referred to as configurators or mass customization toolkits, are one of the most successfully applied

technologies. Examples are the automotive industry, the telecommunication industry, the computer industry, and power electric transformers. Starting with rule-based approaches such as R1/ XCON, model-based representations of knowledge (in contrast to rule-based representations) have been developed that strictly separate product domain knowledge from problem solving knowledge—examples thereof are the

constraint satisfaction problem Constraint satisfaction problems (CSPs) are mathematical questions defined as a set of objects whose state must satisfy a number of constraints or limitations. CSPs represent the entities in a problem as a homogeneous collection of finite const ...

, the

Boolean satisfiability problem In logic and computer science, the Boolean satisfiability problem (sometimes called propositional satisfiability problem and abbreviated SATISFIABILITY, SAT or B-SAT) asks whether there exists an Interpretation (logic), interpretation that Satisf ...

, and different

answer set programming Answer set programming (ASP) is a form of declarative programming oriented towards difficult (primarily NP-hard) search problems. It is based on the stable model (answer set) semantics of logic programming. In ASP, search problems are reduced ...

(ASP) representations. There are two commonly cited conceptualizations of configuration knowledge. The most important concepts in these are components, ports, resources and functions. This separation of product domain knowledge and problem solving knowledge increased the effectiveness of configuration application development and maintenance, since changes in the product domain knowledge do not affect search strategies and vice versa. Configurators are also often considered as "

open innovation Open innovation is a term used to promote an Information Age mindset toward innovation that runs counter to the secrecy and silo mentality of traditional corporate research labs. The benefits and driving forces behind increased openness have b ...

toolkits", i.e., tools that support customers in the product identification phase. In this context customers are innovators who articulate their requirements leading to new innovative products. "Mass Confusion" – the overwhelming of customers by a large number of possible solution alternatives (choices) – is a phenomenon that often comes with the application of configuration technologies. This phenomenon motivated the creation of personalized configuration environments taking into account a customer's knowledge and preferences.

Configuration process

Core configuration, i.e., guiding the user and checking the consistency of user requirements with the knowledge base, solution presentation and translation of configuration results into

bill of materials A bill of materials or product structure (sometimes bill of material, BOM or associated list) is a list of the raw materials, sub-assemblies, intermediate assemblies, sub-components, parts, and the quantities of each needed to manufacture an Prod ...

(BOM) are major tasks to be supported by a configurator. Configuration knowledge bases are often built using proprietary languages. In most cases knowledge bases are developed by knowledge engineers who elicit product, marketing and sales knowledge from domain experts. Configuration knowledge bases are composed of a formal description of the structure of the product and further constraints restricting the possible feature and component combinations. Configurators known as

characteristic based product configurator A characteristic-based product configurator is a product configurator extension which uses a set of discrete variables, called characteristics (or features), to define all possible product variations. Characteristics There are two characteristic ...

s use sets of discrete variables that are either binary or have one of several values, and these variables define every possible product variation.

Software and service configuration

Recently, knowledge-based configuration has been extended to service and software configuration. Modeling software configuration has been based on two main approaches: feature modeling, and component-connectors. Kumbang domain ontology combines the previous approaches building on the tradition of knowledge-based configuration.

References

Conference and journal papers

Books

{{reflist, group="B", refs= U. Blumöhr, M. Münch, M. Ukalovic, Variant Configuration with SAP, Galileo Press, 2012. K. Czarnecki, U. W. Eisenecker, Generative Programming – Methods, Tools, and Applications, Addison Wesley, 2000. A. Felfernig, L. Hotz, C. Bagley, and J. Tiihonen
Knowledge-based Configuration: From Research to Business Cases
Elsevier/Morgan Kaufmann, 2014. C. Forza, F. Salvador, Product Information Management for Mass Customization, Palgrave Macmillan, 2006. L. Hvam, N. Mortensen, J. Riis, Product Customization, Springer Verlag, 2008. F. Rossi, P. Van Beek, T. Walsh, Handbook of Constraint Programming, Elsevier, 2006.