Automated Design of Elevator Systems: Experimenting with Constraint-Based Approaches

System configuration and design is a well-established topic in AI. While many successful applications exists, there are still areas of manufacturing where AI techniques find little or no application. We focus on one such area, namely building and installation of elevator systems, for which we are developing an automated design and configuration tool. The questions that we address in this paper are: (i) What are the best ways to encode some subtasks of elevator design into constraint-based representations? (ii) What are the best tools available to solve the encodings? We contribute an empirical analysis to address these questions in our domain of interest, as well as the complete set of benchmarks to foster further researc

Explainable AI for Constraint-Based Expert Systems

The need to derive explanations from machine learning (ML)-based AI systems has been addressed in recent research due to the opaqueness of their processing.However, a significant amount of productive AI systems are not based on ML but are expert systems including strong opaqueness.A resulting lack of understanding causes massive inefficiencies in business processes that involve opaque expert systems. This work uses recent research interest in explainable AI (XAI) to generate knowledge for the design of explanations in constraint-based expert systems.Following the Design Science Research paradigm, we develop design requirements and design principles. Subsequently, we design an artifact and evaluate the artifact in two experiments. We observe the following phenomena. First, global explanations in a textual format were well-received. Second, abstract local explanations improved comprehensibility. Third, contrastive explanations successfully assisted in the resolution of contradictions. Finally, a local tree-based explanation was perceived as challenging to understand

Industrial Services Characterization for Bidding Process

International audienceWhen responding to call for tenders, many bidding companies offer services. This paper focuses on how to model industrial services during the bidding process to be able to easily develop them. A product offer configuration model is presented, then a reflection about the extension of this model to service offers is conducted. A study of the literature about service definition is dealt and services characteristics are identified. Their impact on the product offer model is analyzed and new characteristics are introduced. This work makes possible to propose a typology to adapt the product offer model to services

Business Process Configuration According to Data Dependency Specification

Configuration techniques have been used in several fields, such as the design of business process models. Sometimes these models depend on the data dependencies, being easier to describe what has to be done instead of how. Configuration models enable to use a declarative representation of business processes, deciding the most appropriate work-flow in each case. Unfortunately, data dependencies among the activities and how they can affect the correct execution of the process, has been overlooked in the declarative specifications and configurable systems found in the literature. In order to find the best process configuration for optimizing the execution time of processes according to data dependencies, we propose the use of Constraint Programming paradigm with the aim of obtaining an adaptable imperative model in function of the data dependencies of the activities described declarative.Ministerio de Ciencia y Tecnología TIN2015-63502-C3-2-RFondo Europeo de Desarrollo Regiona

Designing a Reference Model for Digital Product Configurators

Since the manufacturing industry is nowadays facing increasingly heterogeneous customer requirements, digital product configurators (DPC) have become a popular means for integrating customers into organizational value creation. DPC are information systems, which serve as a frontend to the customer and enable the individualization of products. The design of such a DPC is time consuming, expensive and lacks appropriate models offering guidance for its development. The paper at hand addresses these issues by providing a reference model (RM) for DPC development. The model has been constructed by means of an extensive literature review and was subsequently demonstrated and evaluated in a real world scenario. In order to ensure a flexible and individual development of company specific DPC the RM includes adaptation mechanisms. Therefore, our research provides a first building block to the endeavor of facilitating or even automating DPC development

The KB paradigm and its application to interactive configuration

The knowledge base paradigm aims to express domain knowledge in a rich formal language, and to use this domain knowledge as a knowledge base to solve various problems and tasks that arise in the domain by applying multiple forms of inference. As such, the paradigm applies a strict separation of concerns between information and problem solving. In this paper, we analyze the principles and feasibility of the knowledge base paradigm in the context of an important class of applications: interactive configuration problems. In interactive configuration problems, a configuration of interrelated objects under constraints is searched, where the system assists the user in reaching an intended configuration. It is widely recognized in industry that good software solutions for these problems are very difficult to develop. We investigate such problems from the perspective of the KB paradigm. We show that multiple functionalities in this domain can be achieved by applying different forms of logical inferences on a formal specification of the configuration domain. We report on a proof of concept of this approach in a real-life application with a banking company. To appear in Theory and Practice of Logic Programming (TPLP).Comment: To appear in Theory and Practice of Logic Programming (TPLP

The Impact of Digital Technology on Network Value Co-creation

In recent years, the discussion about how companies integrate new technologies into their value creation and how this affects their business has intensified. The trend towards digitalization is particularly challenging for smaller, value co-creating (VCC) companies in networks, yet little research has been done in this context. In response, this paper identifies four key technologies for promoting network VCC: (1) a service configuration system, (2) a centralized knowledge base, (3) an analytics system, and (4) a shared IT platform. We conducted a single embedded case study in a company network introducing these key technologies and thereby digitally transforming its VCC. Our results show how the companies in the network are approaching their transformation and what the impact and role of the technologies in their network VCC are

Interactive problem solving via algorithm visualization

COMIND is a tool for conceptual design of industrial products. It helps designers define and evaluate the initial design space by using search algorithms to generate sets of feasible solutions. Two algorithm visualization techniques, Kaleidoscope and Lattice, and one visualization of n-dimensional data, MAP, are used to externalize the machine's problem solving strategies and the tradeoffs as a result of using these strategies. After a short training period, users are able to discover tactics to explore design space effectively, evaluate new design solutions, and learn important relationships among design criteria, search speed, and solution quality. We thus propose that visualization can serve as a tool for interactive intelligence, i.e., human-machine collaboration for solving complex problems

An Integrated Knowledge Engineering Environment for Constraint-based Recommender Systems

Abstract. Constraint-based recommenders support customers in identifying relevant items from complex item assortments. In this paper we present a constraint-based environment already deployed in real-world scenarios that supports knowledge acquisition for recommender applications in a MediaWiki-based context. This technology provides the opportunity do directly integrate informal Wiki content with complementary formalized recommendation knowledge which makes information retrieval for users (readers) easier and less timeconsuming. The user interface supports recommender development on the basis of intelligent debugging and redundancy detection. The results of a user study show the need of automated debugging and redundancy detection even for small-sized knowledge bases