Performance Measurement for Robust and Agile Scheduling and Control of Industrial Product-Service Systems

Abstract In the manufacturing industry competitors are continuously struggling to differentiate from other companies in the market. Industrial Product- Service Systems (IPS 2 ) offer this differentiation by representing a paradigm shift from traditional product selling and service offering to providing customer value. To support the IPS 2 provider during the delivery and use phase of IPS 2 an IPS 2 -Execution System (IPS 2 -ES) has been developed. The system is needed for planning, scheduling and organization of the required delivery processes and the partner network. In addition to that, a performance measurement method for IPS 2 (IPS 2 -PMM) supports the IPS 2 provider with an evaluation of the IPS 2 delivery through key performance indicators (KPI). For the holistic agile scheduling and control for IPS 2 delivery, an IPS 2 control model has been developed. However, to add robustness for the IPS 2 delivery, the IPS 2 -PMM has to be integrated into this model. In this paper, the IPS 2 control model is extended to allow for an integration of the IPS 2 -PMM. Thus, the cascaded control loops are enriched by the generation of KPI for the evaluation of the IPS 2 delivery.

[1]  H. Meier,et al.  Industrial Product-Service Systems—IPS2 , 2010 .

[2]  Friedrich Morlock,et al.  Delivery management of industrial product-service systems – challenges for a performance measurement , 2013 .

[3]  Nicholas R. Jennings,et al.  A methodology for agent-oriented analysis and design , 1999, AGENTS '99.

[4]  Anke Giese.  Differenziertes Performance Measurement in Supply Chains , 2012 .

[5]  Oksana Mont,et al.  Clarifying the Concept of Product-Service System , 2002 .

[6]  Jan Marco Leimeister,et al.  Dienstleistungsengineering und -management , 2012 .

[7]  George Chryssolouris,et al.  Manufacturing Systems: Theory and Practice , 1992 .

[8]  Friedrich Morlock,et al.  Architecture and Conceptual Design for IPS2-Execution Systems , 2013 .

[9]  V. Sugumaran,et al.  Tool condition monitoring using K-star algorithm , 2014, Expert Syst. Appl..

[10]  M. Rese,et al.  An Ontology of Business Models for Industrial Product-Service Systems , 2013 .

[11]  Oliver Völker,et al.  Industrial Product-Service Systems (IPS2) , 2011 .

[12]  Horst Meier,et al.  Agile Scheduling and Control for Industrial Product-service Systems , 2013 .

[13]  Friedrich Morlock,et al.  Data Interfaces of IPS2-Execution Systems – Connecting Virtual Organization Units for the Delivery Management of IPS2 , 2014 .

[14]  Friedrich Morlock,et al.  Key performance indicators for assessing the planning and delivery of industrial services , 2013 .

[15]  Barbara Linke,et al.  Leveraging Technology for a Sustainable World , 2012 .

[16]  Dimitris Mourtzis,et al.  Development of methods and tools for the design and operation of manufacturing networks for mass customisation , 2016 .

[17]  Roy Fielding,et al.  Architectural Styles and the Design of Network-based Software Architectures"; Doctoral dissertation , 2000 .

[18]  Friedrich Morlock,et al.  Concept for a Performance Measurement Method for the Organization of the IPS2 Delivery , 2014 .

[19]  Oliver Völker,et al.  Aufbau- und Ablauforganisation zur Erbringung hybrider Leistungsbündel , 2012 .

[20]  Erkki Jantunen,et al.  A summary of methods applied to tool condition monitoring in drilling , 2002 .

[21]  R. S. Kaplan,et al.  Balanced scorecard : strategien erfolgreich umsetzen , 1997 .

[22]  Eckart Uhlmann,et al.  Flexible Implementation of IPS2 through a Service-based Automation Approach☆ , 2013 .

[23]  Marion Steven,et al.  Risk Management of Industrial Product-Service Systems (IPS2) – How to Consider Risk and Uncertainty over the IPS2 Lifecycle? , 2012 .

[24]  E. Uhlmann,et al.  IPS2 Control System for the Integrated Support of Service Processes , 2013 .