Michael Lieder

An event-driven manufacturing information system architecture for Industry 4.0

Future manufacturing systems need to be more flexible, to embrace tougher and constantly changing market demands. They need to make better use of plant data, ideally utilising all data from the entire plant. Low-level data should be refined to real-time information for decision-making, to facilitate competitiveness through informed and timely decisions. The Line Information System Architecture (LISA), is presented in this paper. It is an event-driven architecture featuring loose coupling, a prototype-oriented information model and formalised transformation services. LISA is designed to enable flexible factory integration and data utilisation. The focus of LISA is on integration of devices and services on all levels, simplifying hardware changes and integration of new smart services as well as supporting continuous improvements on information visualisation and control. The architecture has been evaluated on both real industrial data and industrial demonstrators and it is also being installed at a large automotive company. This article is an extended and revised version of the paper presented at the 2015 IFAC Symposium on Information Control in Manufacturing (INCOM 2015). The paper has been restructured in regards to the order and title of the chapters, and additional information about the integration between devices and services aspects have been added. The introduction and the general structure of the paper now better highlight the contributions of the paper and the uniqueness of the framework.

Towards Circular Economy implementation: an agent-based simulation approach for business model changes

This paper introduces an agent-based approach to study customer behavior in terms of their acceptance of new business models in Circular Economy (CE) context. In a CE customers are perceived as integral part of the business and therefore customer acceptance of new business models becomes crucial as it determines the successful implementation of CE. However, tools or methods are missing to capture customer behavior to assess how customers will react if an organization introduces a new business model such as leasing or functional sales. The purpose of this research is to bring forward a quantitative analysis tool for identifying proper marketing and pricing strategies to obtain best fit demand behavior for the chosen new business model. This tool will support decision makers in determining the impact of introducing new (circular) business models. The model has been developed using an agent-based modeling approach which delivers results based on socio-demographic factors of a population and customers’ relative preferences of product attributes price, environmental friendliness and service-orientation. The implementation of the model has been tested using the practical business example of a washing machine. This research presents the first agent-based tool that can assess customer behavior and determine whether introduction of new business models will be accepted or not and how customer acceptance can be influenced to accelerate CE implementation. The tool integrates socio-demographic factors, product utility functions, social network structures and inter-agent communication in order to comprehensively describe behavior on individual customer level. In addition to the tool itself the results of this research indicates the need for systematic marketing strategies which emphasize CE value propositions in order to accelerate customer acceptance and shorten the transition time from linear to circular. Agent-based models are emphasized as highly capable to fill the gap between diffusion-based penetration of information and resulting behavior in the form of purchase decisions.

Resource Efficiency Assessment System

Resource efficiency has become a topic of greater importance due to dramatic increase of world-population and globalization. A company that is not able to efficiently utilize its resources is less sustainable and competitive. This paper introduces an assessment approach as a tracking and analyzing system to facilitate improvement of resource efficiency particularly for SMEs. The approach supports common economic KPIs of producing companies using resource-based measures. Two main elements are used. One for tracking resource efficiency measures (REC) and one for analyzing efficiency losses (REF). A tool has been designed to support the application and interpretation of the system elements.