Showing papers in "Concurrent Engineering in 2023"
TL;DR: In this article , the grey system theory in artificial intelligence technology combined with QFD to develop grey-QFD to solve the issues mentioned before, and the grey relationship analysis established the aesthetic product design matrix between CRs and ECs, and calculated and ranked the final weights of each ECs by using grey relationship degree.
Abstract: Quality function deployment (QFD) is a systematic approach to transform customer requirements (CRs) into product engineering characteristics (ECs). Traditional QFD relies on market research or customer questionnaires to collect a series of ambiguous and uncertain CRs. As a result, evaluating the weighting of CRs and determining the design matrix between CRs and ECs have become the focus and difficulty of QFD. This paper proposes the grey system theory in artificial intelligence technology combined with QFD to develop grey-QFD to solve the issues mentioned before. First, collect the average evaluation values between the aesthetic images and customer satisfaction of representative products. The grey prediction GM (1, N) model is used to obtain the weight of aesthetic needs relative to customer satisfaction and import it into the left QFD. Second, the domain experts decomposed the product form into a morphological analysis table, and fuzzy Delphi screened key ECs and imported them into the ceiling of QFD. Finally, grey relationship analysis established the aesthetic product design matrix between CRs and ECs, and calculated and ranked the final weights of each ECs by using grey relationship degree. The research uses the security camera in the smart home as an experimental object. After operating the proposed grey-QFD, the aesthetic quality of the target product (lively, intelligent, friendly, personalized, and fashionable) and the optimization of the corresponding product ECs are obtained. The result provides a theoretical reference for designers and significantly improves customer aesthetic satisfaction.
7 citations
TL;DR: A method for model-based Trade-off Curves (ToC) generation to support Set-Based Concurrent Engineering (SBCE) and presented the state-of-the-art in ToC generation and application, proposing the model and demonstrating SBCE in highly innovative projects.
Abstract: The literature acknowledges the advantages of Set-Based Concurrent Engineering (SBCE), but there is a lack of models for its adoption and documented cases of its implementation, mostly on products with consolidated technology, which raises the possibility of expanding SBCE for highly innovative products. These projects often have extensive resource limitations, leading to computational tools and mathematical modelling as fundamental sources of information. This paper proposes a method for model-based Trade-off Curves (ToC) generation to support SBCE. We adopted it to develop a magnetic air conditioner. The use of model-based ToC enabled the narrowing of the design space and monitoring of the design parameters and performance metrics and enabled SBCE adoption in the design process. The main contributions of this research are presenting the state-of-the-art in ToC generation and application, proposing the model, and demonstrating SBCE in highly innovative projects, while its importance lies in the opportunity to further disseminate SBCE to different development environments.
2 citations
TL;DR: Data-driven product optimization capabilities enhance sustainability and environmental compliance in a marine manufacturing context by improving decision-making and streamlining processes through accurate data and digital thread creation.
Abstract: This paper investigates concerns related to product data and digital data flow when aiming to automate company processes. Accurate data is necessary to create value by enabling improved decision-making in product development, including sustainability capabilities. The case analyzed is an engineer-to-order (ETO) company operating in a low-volume marine manufacturing context. A participatory research approach is used to study two projects that are part of the company’s digital business transformation, aiming to digitalize information and autogenerate downstream processes. Building on the strengths promised by digitalization requires precise and extensive product and process information. An important facilitation capability is to create a digital thread from design to finished product, including product documentation. This is necessary to establish capabilities both to autogenerate appropriate compliance reporting as part of the product development process and to conduct virtual testing and validation before the physical equipment is acquired, resulting in a manufacturing process that is ‘right first time’. In addition, data capabilities guide and enable sound-decision making for improved sustainable practices in the early phase of product development. It is found that the data quality required to utilize tools within the context of Industry 4.0 demands changes to existing product design practices and focus on the three pillars harmonization, integration and automation of data and systems.
TL;DR: The NPD project management literature has grown significantly in the past decade. Key research themes include optimization and simulation, knowledge management, product innovation, performance and success factors, and development strategy and firm strategy.
Abstract: The research in relation to new product development (NPD) project management has been very rich in the past decade. However, there has been a lack of quantitative literature reviews investigating the status and evolution of research. In this study, we aimed to fill this gap by reviewing the NPD project management literature in the SCI-E and SSCI databases from 2012 to 2021 using the bibliometric method and the CiteSpace tool. First, we provided an overview of publications and identified several leading journals. Second, based on a keyword co-occurrence network, we identified five important research themes in NPD project management: optimization and simulation, knowledge management, product innovation, performance and success factors, and development strategy and firm strategy. Furthermore, we reviewed the important literature relating to each theme. Third, we analyzed the evolution of the NPD project management literature, as well as identifying research hotpots in the last 10 years, by creating a keyword time zone network. Finally, we proposed future trends in NPD project management research to fill the existing gaps.
TL;DR: Simulation analysis showed that the more sensitive the SP was to the transaction activity in the system, the earlier the ecosystem in which it was located enters the stable period, and the evolution trend of CMSE would show an obvious turning point from rapid growth to shrinkage.
Abstract: Monitoring and evaluating the health of the cloud manufacturing service ecosystem (CMSE) is critical to ensuring the long-term development of the cloud manufacturing service platform. The behavior patterns of three types of market entities, service demander (SD), service provider (SP) and platform operator (PO), have an important impact on the evolution trend of CMSE. The formulation of platform transaction rules and development of operation and regulation strategies need clarified the evolution law of the CMSE. Therefore, the evolution framework of the CMSE is constructed, the behavior modes of market entities such as SP, SD, and PO are established respectively, and multi-agent behavior simulation experiments are carried out. Simulation analysis showed that the more sensitive the SP was to the transaction activity in the system, the earlier the ecosystem in which it was located enters the stable period. When the sensitivity k of SD to the number of SPs that are available for required services in the system was between 0.45 and 0.5, the evolution trend of CMSE would show an obvious turning point from rapid growth to shrinkage. PO could adopt flexible charging strategies at different stages of the evolution of the CMSE to maximize revenue.
TL;DR: The paper identifies challenges and solutions for collaboration between manufacturing SMEs through a collaborative platform based on the business model canvas. Six challenges are identified and solutions are suggested.
Abstract: Innovation, open innovation, and collaborative platforms are concepts in effervescence in the last few years. Innovation’s future will observe a growing number of collaborations. The links between collaboration and collaborative platforms are known in the transport and accommodation sector (such as Uber) however are less used in manufacturing. This paper aims to identify the main challenges between manufacturing firms which intend to collaborate enabled by a prototype platform. A collaborative business model was designed using the business model canvas and tested using a real case to generate valuable collaboration. Collaboration experimentation was monitored over 21 weeks between two firms of the Quebec aerospace cluster and ended with a semi-structured interview. Six challenges were identified: partner selection, commitment and trust, intellectual property management, collaboration evaluation, collaboration symmetry and terminology difficulties. Suggested solutions included, compatibility criteria between the partners, creating a vocabulary lexicon, and establishing collaboration expectations prior to collaboration.