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With the upcoming age of IoT [35, 43, 45] and CPS [46], Industry 4.0 redefines the industrial manufacturing system in a completely automated scenario. The characteristics of “digitization, intelligentization, and customization” of this industrial evolution advance the traditional manufacturing techniques from mass production towards a deep‐rooted mass‐customization (MC) [47].

Although MC is not a new concept, it is emphasized again in Industry 4.0 for the fact that customers are returning to the center of the core value [48, 49]. One of the core values of Industry 4.0 targets to integrate people’s demand into manufacturing for enhanced products, systems, and services for a wider variety of increasingly personalized customization of products [49]. Thus, a further change will happen to the manufacturing industries with Industry 4.0 that the customers can benefit from [50].

Frankly, it is the birth of IoT/CPS that lifts data‐collection and communication technologies to a new level so as to allow a faster response to customers’ needs. Industrial manufacturers can efficiently build relationships with the end‐customers by combining the flexibility and personalization of “custom‐made” in real‐time. MC is also known as the concept of “made to order” or “build to order” [51]. The production only happens after manufacturers know what customers’ demands are. Customers or end‐users can easily decide the certain functionalities or personal attributes of a unique product or service what they exactly want just via a web portal. In other words, customers, manufacturers, and equipment closely interact with one another through seamless connections via IoT/CPS – a win‐win situation for all participants in modern manufacturing relationships.

MC aims to provide customers with varieties of increasing customized products and a near mass‐production efficiency without the corresponding increase in cost and lead time. Since MC first coined by Davis [52], it has attracted a large number of researchers to take their great efforts to make MC possible for decades. So far there has been a significant progress, such as Gilmore and Pine [53] defined four approaches: collaborative, adaptive, cosmetic, and transparent customizations for targeting different mass consumer groups in MC markets depending on degrees of customization in the product itself, and representation of the product. Collaborative customization seeks to help clients who struggle to spot exactly what they want and helps to understand the needs of the customers and strives to make it clear to them. Adaptive customization allows customers to handle customized products themselves without manufacturer’s assistance. Cosmetic customization presents a standard product with various representation to different customers. Transparent customization means that manufacturers provide unique products without needing to inform customers. Silveira et al. [54] surveyed the earlier studies on MC to point out the visionary and practical conceptualizations of MC theory; also, fundamental requirements for developing a basic MC framework composed from eight generic levels of MC were thoroughly discussed in [54]. Further, as information technologies evolves, Fogliatto et al. [55] updated the latest successful MC applications among various fields, including the food industry, electronics, large engineered products, mobile phones, and personalized nutrition; or special MC applications such as homebuilding and the production of foot orthoses. They clearly identified required conditions in different fields and situations of implementing a suitable MC platform from the view of economics, success factors, enablers, and customer‐manufacturer interactions.

For manufacturers, two mandatory factors of agility and quick responsiveness to manufacturing changes are expected to minimize the escalating costs [51, 53, 55]. They have to ensure the production facility must be flexible enough for switching between complex variants with some delay and be agile enough to adapt to changes in customized products at a low cost, thereby retaining economic benefits [55, 56]. For customers, after the emergence of Industry 4.0, the state‐of‐the‐art of IoT/CPS replaces traditional MC scenarios, and gives customers more chances to actively participate in a collaborative design of customized products.

However, no matter how production technologies are improved in the era of Industry 4.0, the ultimate aim for manufacturing has not changed, which is the manufacturing quality of products. Manufacturers are imperative to ensure that the manufacturing quality of deliverables conforms to the design specifications before delivering them to customers. Thus, “quality control” is also listed as one of the promising areas to be achieved for future research in MC [55]. Namely, how to effectively minimize the defective product cost is still the biggest challenge of MC. As such, a fully automated and real‐time total‐inspection method is needed to withstand a global requirement on increasing product quality and reducing production cost.