## 5 Conclusions  
In the context of Industry 4.0, it is urgent for the service providers to meet dynamic customer requirements with a short response time. Thus, this study adopted a sophisticated mechanism to swiftly optimize customer satisfaction in a feasible and reasonable manner. In addition, a case study was conducted to elaborate how the product configuration system could be adopted in the order acquisition and fulfillment process for SME in the context of laptop configuration. This study helps to significantly reduce errors in the configurations released by the sales department through the  
Figure 10: ‘To-be’ process of order acquisition and quick response process with OrderAssistant. Figure 9: The upgraded recommendation of OrderAssistant based on sensitive analysis. implementation of the product configuration system under Industry 4.0. It is capable of handling a large volume of information exchanged between the frontend and backend departments with greater accuracy and efficiency, recovering a considerable amount of manpower spent on the traditional manual activities over the long run. Furthermore, it serves as a database to store product knowledge and all historical configurations for different user groups, accumulating intangible but valuable assets to the organization for future reference. In summary, this study provides the following contributions. First, this is pioneering work in developing a quick response product configuration system, implementing the MTO and mass customization strategy in the context of Industry 4.0. Though Industry 4.0 enables smart manufacturing and smart factories, a product configuration system is necessary to bridge the gap between customers and manufacturers. It is expected that the proposed concept could augment the potential of Industry 4.0 in meeting dynamic user requirements. Second, this study made a breakthrough in modifying the QFD approach. Instead of roughly considering the relationship between CRs and ECs, the authors considered the smaller elements of the relationship, reflecting on the role of EC in each CR better than before. In this way, the optimization model is robust to evaluate more than one feature for each EC and solve more practical problems. Third, this study opens the door of using quantitative analysis, such as the Kano model or QFD approach, in the context of a product configuration system, integrating mathematical approaches into the traditional design process by presenting a customization framework on a larger scale--from product database definition to customer satisfaction quantification, optimization modelling, and finally sensitivity analysis. Pioneer work of developing a quick-response product configuration system under Industry 4.0, applying customer requirement modelling, and an optimization method was demonstrated. Meanwhile, the novelty and advantages are summarized below:  
* Engineering characteristics and voice of users are taken into consideration by the proposed design model for quick-response product configuration system in a systematic way. Thus, an in-context, customer centric, and optimization-oriented quick-response product configuration system under Industry 4.0 context was first carried out in this holistic and generalized manner. * The empirical case study explored a real production (to-be) scenario among an international manufacturing solution supplier, a SME manufacturing service provider and a SME service demander. * Moreover, in this scenario, the transformation between as-is process and to-be process with the new quick response product configuration system: OrderAssistant were clearly identified and described. A novel prototype developed by incorporating with Kano, QFD, and optimization model was first proposed in the research of Industry 4.0 and smart manufacturing area. Generally, this study enriched the literature of Industry 4.0 application with the product configuration system as well as advanced a step in using integrated approaches to establish a new product configuration model.