Abstract

In response to rapidly changing market and customer needs, product design and development (PDD) is evolving into a human-centred and data-driven design paradigm. The design environment gets more open often involving crowdsourcing and the design process becomes more complex, considering product family design along product whole lifecycle development, and needing more data support. Therefore, it is critical to effectively capture, share, and manage design-related information in such a complex design environment. From this perspective, it is a prerequisite to have a proper product design lifecycle information model (PDLIM) to guide information gathering, sharing and management. To the best of our knowledge, currently, there lacks such a PDLIM to support effective PDD, though digital twin (DT) technology shows a great potential of supporting product lifecycle information collection and management. In this paper, the overall structure of the proposed PDLIM is firstly developed to frame in all main product lifecycle stages and the corresponding key phases for structurally capturing and storing necessary data along a product lifecycle. Secondly, key design information items against the main product lifecycle stages and their corresponding key phases are explored from literature reviews and case study analyses. Thirdly, the necessity of the identified information items in the PDLIM is qualitatively evaluated by two case studies. Finally, the PDLIM is further evaluated by applying formal object-role modelling (ORM) to demonstrate how design information items are used and interacted in exemplary design interaction scenarios, and to approve that it can be formally described and managed as an information model. The evaluation results show that the PDLIM is feasible to be adapted in a crowdsourcing-combined PDD process for supporting design management, reviewing, quality control, and next round product redesign and improvement.

Highlights

  • With customer needs and market demands continually evolving and shifting over time, small and medium enterprises (SMEs) in manufacturing face a great demand for a variety of new products in a short time [1, 2]

  • As the data/information collection, analysis, and modelling have been relatively well studied [18, 19], this paper mainly focuses on what information should be collected in the product lifecycle in in-house and crowdsourcing combined design environments

  • This paper proposed a new product design lifecycle information model (PDLIM) enabling product throughlife design and development trends under an in-house and crowdsourcing combined design environment

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Summary

Introduction

With customer needs and market demands continually evolving and shifting over time, small and medium enterprises (SMEs) in manufacturing face a great demand for a variety of new products in a short time [1, 2]. To effectively support the above design trends, product usage data are required to be acquired and analyzed in a real-time manner and all design information over the product lifecycle is required to be seamlessly captured, stored, and retrieved for information sharing and communication among all involved departmental teams and crowds in combined design environments. A product generated real performance data (most likely differing from the simulated design data) during the product in-use stage is excluded, making it hard to monitor the product real-time performance and predict required maintenance based on that To our knowledge, these existing models are unable to support a holistic product design and development process requiring necessary data/information support through the product whole lifecycle. We believe that this PDLIM is critical in supporting the above three emerging PDD trends It is a prerequisite for practising a holistic and sustainable design process through effective integration with other key product lifecycle development stages.

Development of the PDLIM
The overall structure of PDLIM
Key design information exploration
Design environment associated information
Associated information in traditional in-house design environment
Associated information in crowdsourcing design environment
PDLIM application scenarios and potential benefits
Qualitative evaluation of identified information items in the PDLIM
Case study 1—“Redesigning the food processor”
Design concept
Case study 2—“The design of dockless sharing bikes”
Modelling information interaction in the PDLIM
Design representation model and its mapping with PDLIM
Information interaction models in typical scenarios
Conclusion and future work
Findings
Data availability None
Full Text
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