Traditionally, small and medium enterprises (SMEs) in manufacturing rely heavily on a skilled, technical and professional workforce to increase productivity and remain globally competitive. Crowdsourcing offers an opportunity for SMEs to get access to online communities who may provide requested services such as generating design ideas or problem solutions. However, there are some barriers preventing them from adopting crowdsourcing into their product design and development (PDD) practice. In this paper, we provide a literature review of key crowdsourcing technologies including crowdsourcing platforms and tools, crowdsourcing frameworks, and techniques in terms of open call generation, rewarding, crowd qualification for working, organization structure of crowds, solution evaluation, workflow and quality control and indicate the challenges of integrating crowdsourcing with a PDD process. We also explore the necessary techniques and tools to support the crowdsourcing PDD process. Finally, we propose some key guidelines for coping with the aforementioned challenges in the crowdsourcing PDD process.
Small and medium-sized enterprises face the challenges that they do not have enough employees and related resources to produce high-quality products with limited budget and time. The emergence of crowdsourcing provides an opportunity for them to improve their products by leveraging the wisdom of a large community of crowds, including their potential customers. With this new opportunity, product design could be conducted partially in a traditional design environment (in-house design) and partially in a crowdsourcing environment. This article focuses on product design stages to investigate what key factors affect product design quality and how it can be controlled and assured. First, we define the concept of product design quality and then identify its attributes and sub-attributes. Second, we separately survey key factors affecting product design quality in traditional and crowdsourcing-based design environments, quality control approaches/theories and quality assurance policies in traditional design environment. Third, a comparison of product design quality issues between the traditional and crowdsourcing-based design environments is progressed focusing on various aspects influencing product design activity quality. Finally, we discuss product design quality control approaches and quality assurance policies, quality control challenges and corresponding solutions in crowdsourcingbased design environment.
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.
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