Twenty-Five Years of Successful Application of Constraint Technologies at Siemens

AI Magazine

The development of problem solvers for configuration tasks is one of the most successful and mature application areas of artificial intelligence. The provision of tailored products, services, and systems requires efficient engineering and design processes where configurators play a crucial role. For more than 25 years the application of constraint-based methods has proven to be a key technology in order to realize configurators at Siemens. This article summarizes the main aspects and insights we have gained looking back over this period.



In this work, we particularly focus on the complex relationship between land-use and transport offering an innovative approach to the problem by using land-use features at two differing levels of granularity (the more general land-use sector types and the more granular amenity structures) to evaluate their impact on public transit ridership in both time and space. To quantify the interdependencies, we explored three machine learning models and demonstrate that the decision tree model performs best in terms of overall performance--good predictive accuracy, generality, computational efficiency, and "interpretability". We then demonstrate how the developed framework can be applied to urban planning for transit-oriented development by exploring practicable scenarios based on Singapore's urban plan toward 2030, which includes the development of "regional centers" (RCs) across the city-state. This trend, on the other hand, eventually reverses (particularly during peak hours) with continued strategic increase in amenities; a tipping point at 55% increase is identified where ridership begins to decline and at 110%, the predicted ridership begins to fall below current levels.

Recommendation Technologies for Configurable Products

AI Magazine

State of the art recommender systems support users in the selection of items from a predefined assortment (for example, movies, books, and songs). In contrast to an explicit definition of each individual item, configurable products such as computers, financial service portfolios, and cars are repre sented in the form of a configuration knowledge base that describes the properties of allowed instances. Although the knowledge representation used is different compared to non-confi gurable products, the decision support requirements remain the same: users have to be supported in finding a solution that fits their wishes and needs. In this article we show how recommendation technologies can be applied for supporting the configuration of products.

A Framework for the Development of Personalized, Distributed Web-Based Configuration Systems

AI Magazine

For the last two decades, configuration systems relying on AI techniques have successfully been applied in industrial environments. These systems support the configuration of complex products and services in shorter time with fewer errors and, therefore, reduce the costs of a mass-customization business model. The European Union-funded project entitled CUSTOMER-ADAPTIVE WEB INTERFACE FOR THE CONFIGURATION OF PRODUCTS AND SERVICES WITH MULTIPLE SUPPLIERS (CAWICOMS) aims at the next generation of web-based configuration applications that cope with two challenges of today's open, networked economy: (1) the support for heterogeneous user groups in an open-market environment and (2) the integration of configurable subproducts provided by specialized suppliers. This article describes the CAWICOMS WORKBENCH for the development of configuration services, offering personalized user interaction as well as distributed configuration of products and services in a supply chain.

A Knowledge-Based Configurator that Supports Sales, Engineering, and Manufacturing at AT&T Network Systems

AI Magazine

PROSE is a knowledge-based configurator platform for telecommunications products. Its outstanding feature is a product knowledge base written in C-classIC, a frame-based knowledge representation system in the KL-ONE family of languages. Unlike previous configurator applications, the PROSE knowledge base is in a purely declarative form that provides developers with the ability to add knowledge quickly and consistently. The PROSE architecture is general and is not tied to any specific telecommunications product.

R1: The Formative Years

AI Magazine

R1 is a rule-based program that configures VAX-11 computer systems. Given a customer's purchase order, it determines what, if any, substitutions and additions have to be made to the order to make it consistent and complete and produces a number of diagrams showing the spatial and logical relationships among the 90 or so components that typically constitute a system. The program has been used on a regular basis by Digital Equipment Corporation's manufacturing organization since January of 1980. R1 has sufficient knowledge of the configuration domain and of the percliarities of the various configuration constraints that at each step in the configuration process, it simply recognizes what to do; thus it requires little search in order to configure a computer system.