Set-Based Concurrent Engineering Innovation Roadmap (SBCE IR): a case on Adiabatic Humidification System

Abstract

Set-Based Concurrent Engineering (SBCE) is an element of lean practice in product development (PD), and it is composed of principles to apply it at early phase of a design process. However, executing the principles demands extensive efforts in practice. Thus, a systematic methodology is required to identify and prioritize potential areas (area in this paper is a generic term used to refer to subsystems, components or design factors or parameters a designer is applying SBCE process to explore, communicate and evaluate sets of solutions to satisfy a customer requirement or to solve a particular problem) where SBCE brings its utmost benefits. This paper proposes such a methodology called SBCE Innovation Roadmap (SBCE IR) that is used as a guideline by product designers to begin SBCE processes. A case study on Adiabatic Humidification System (AHS) is discussed to elaborate the application of the methodology in a real product system. Furthermore, by using the roadmap, a rack subsystem is selected to show how to use SBCE IR as an input for SBCE process, and further explore and evaluate innovative design concepts. Finally, an open questionnaire is prepared and interviews are made with experts to assess the advantages, applicability, and limitations of the methodology.

Keywords::

• Set-Based Concurrent Engineering
• Quality Function Deployment
• Theory of Inventive Problem Solving
• contradictions
• Adiabatic Humidification System

Acknowledgements

This research has been conducted as part of a European project titled “Lean Product and Process Development (LeanPPD)” (NMP-2008-214090). The authors acknowledge the European Commission for its financial support and the project's partners for their comments and suggestions during the preparation of this paper. Moreover, the authors thank managers and designers at Carel Industries that who been involved in the research.

Notes

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^4. Email: [email protected]

^5. The causal relations can be read from matrix obtained using Equation (6). To determine whether relationships between contradictions are strong, a threshold matrix should be defined. For example, some authors suggest a threshold of 0.2 (Lee et al., 2010). Those contradictions that have more than or equal to 0.2 relations coefficients in the matrix can be considered to have strong relations.

Additional information

Funding

This work was supported by The European Commission [grant number 214090].