Identification of the cost-benefit-optimal product configuration

Schuh, Guenther; Doelle, Christian; Koch, Jan; Grutza, Pascal

doi:10.1016/j.procir.2018.03.294

Cited by 4 publications

(3 citation statements)

References 8 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Based on those researches of design method and the integration with modularization, product configuration becoming the effective means for personalized customization. Schuh et al proposed an optimal product configuration method to balance the benefits and cost growth of enterprise, which are brought by variant products in the configuration process (Schuh, Doelle, and Koch et al 2018). Jiao et al trained intelligent classifier with customer evaluation data to realize the selection of final product configuration scheme (Jiao and Yang 2019).…”

Section: Introductionmentioning

confidence: 99%

Whole lifecycle evolution control method of modular product structure oriented to personalized service

Jiang

Zhou

Ping-lu

et al. 2021

International Journal of Computer Integrated Manufacturing

View full text Add to dashboard Cite

The modular product structure is the orderly integration of the information generated by the modular design. With the deepening of the personalized service concept, in order to better provide personalized product customization services driven by customer demands, the research of modular product structure evolution control in the whole lifecycle is extremely necessary. Considering the different concerns of the tasks in different stages of the whole lifecycle, a 4-level modular product structure whole lifecycle evolution modelling system is proposed to transform the modular product structure into different tree structure for each lifecycle stage. By modelling the attributes for the nodes and the relationship for the edges of each stage tree, the standardized management and invocation of the information required by the personalized service process is realized. On this basis, two different personalized product customization methods led by recommendation or configuration are proposed, and the flow path and algorithm writing logic of personalized product configuration are introduced based on each stage tree. Finally, the method is applied to small agricultural machinery (SAM) products, which proves that the method can reasonably and orderly controls the evolution process, and provides a new idea for the development of whole lifecycle personalized services.

show abstract

Section: Introductionmentioning

confidence: 99%

Whole lifecycle evolution control method of modular product structure oriented to personalized service

Jiang

Zhou

Ping-lu

et al. 2021

International Journal of Computer Integrated Manufacturing

View full text Add to dashboard Cite

show abstract

“…These investments tend to grow with the increasing of markets served by the company. Economically it is not feasible since the costs of development and production of different products demand high costs for the company [1].…”

Section: Introductionmentioning

confidence: 99%

Product Platform: Trends and Opportunities

Cerqueira

Voltolini

Borsato

2019

Advances in Transdisciplinary Engineering

View full text Add to dashboard Cite

Increasing market competitiveness forced industries to seek ways to reduce production costs and increase profitability. Companies operating in different markets face different customer expectations. Thus, it is necessary to develop products that meet the most varied market requirements, without demanding the high investment costs that product customization demands. The development of product platforms has helped companies to lower the cost of mass customization. The main benefit of using platforms is the reduction of investment in customized product development. A platform allows creating specific product families for each market application. In view of this context, a bibliographical review was performed with the objective of finding the state of art for the theme and mapping the research opportunities. For this activity, the research tool ProKnow-C (Knowledge Development Process – Constructivist) was considered. From a quantitative analysis, the most relevant papers were identified, based on authors, periodicals, the relevance of articles and keywords. Then, the systemic analysis of articles related to the theme evidences the frontiers of knowledge. The main objectives, methodologies, and opportunities for future research were mapped from 33 articles selected from the database. In the end, 3 gaps were identified for future work.

show abstract

“…The complexity of use cases prevents humanengineered deductive rule-based approaches. Moreover, the complexity requires data-driven approaches to automatically find correlations in data [399]. Furthermore, JTS for high-variety industries with continuous development does not necessarily require a true optimal result for individual scenarios.…”

Section: Joining Technology Selectionmentioning

confidence: 99%

Automated joining element design for high product variety in the manufacturing industry

Eggink

View full text Add to dashboard Cite

Product variety and the manufacturing complexity that it induces are continuously increasing. This poses a challenge in the product development process and, consequently, the design of joints. Joining elements define the manner in which a permanent joint is created between parts. Joining element design is an ambiguous manual task with limited automation solutions. Thus, it can lead to long, iterative, error-prone development trajectories that may result in costly rework. Hence, automation solutions for joining element design must be intelligent. However, simply ensuring the intelligent automation of joining element design is insufficient. Modular design, through the approaches of modularization and commonalization, enables manufacturers to cope with the complexity induced by product variety. Unfortunately, modular design approaches have not yet considered joining elements. Hence, this dissertation study sought to answer the following research question: "How can joining element design be automated for high-variety products?"This dissertation presents a framework for automating joining element design. The framework is structured into smaller design problems, which will guide designers through the process of designing joining elements. This structuring will also enable designers to evaluate and assess artificial intelligence (AI) for each design problem. Moreover, the design problems will enable designers to identify unused AI techniques, such as machine learning.These techniques were conceptualized and several were implemented for validation in this study. A market-validated database with automotive Body-in-White structures was used. The validation included the use of decision trees to predict joining technologies and the number of joining elements. Both prediction tasks seem promising to implement in early design phases due to their simplicity.Next, this study validated two approaches for predicting joining locations. The first was a straight-forward evolutionary algorithm for distributing spot welds over contact regions. However, this algorithm's performance fell off quickly for nontrivial design problems with high solution spaces.The second approach was to use convolutional neural networks to predict spot weld locations, which provided robust and promising results. This study first explored a voxel-based regression and classification task by drawing locations in a grid-like structure. Classification with a segmentation approach produced more robust results due to the spatial dependencies of classes. Supervised machine learning enabled the consideration of knowledge of successful designs in new design problems. This concept was subsequently enriched with nongeometric data using a branding approach. However, these multimodal machine learning models did not improve the joining locations. Furthermore, the models could not extract the i ii

show abstract

Identification of the cost-benefit-optimal product configuration

Cited by 4 publications

References 8 publications

Whole lifecycle evolution control method of modular product structure oriented to personalized service

Whole lifecycle evolution control method of modular product structure oriented to personalized service

Product Platform: Trends and Opportunities

Automated joining element design for high product variety in the manufacturing industry

Contact Info

Product

Resources

About