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Manufacturing industries are moving towards mass personalization, which refers to the rapid production of individualized products, with large scale efficiencies. This shift from push-type mass customization to pull-type mass personalization will pose critical operational challenges to manufacturing businesses, with complexities ranging from effective requirements elicitation to design, manufacturing, commissioning and after-sales support. Aiming at addressing these challenges, a feasible operational framework for enabling efficient manufacturing automation for mass personalization is proposed in this paper. A key element of this operational framework is the Digital Thread, which streamlines information flow associated with design, manufacturing, maintenance and servicing of a personalized product, each of which are represented as Digital Twins. An As-Designed Digital Twin is created from the beginning of the product co-design process, which then evolves into the subsequent design and manufacturing process and systems resulting in As-Designed Digital Twin evolving to As-Planned Digital Twin and then to As-Built Digital Twin. The personalized product, after it’s commissioning and installation constitutes the As-Maintained Digital Twin of the product, which stores product data related to field performance. The data exchange and communications between these Digital Twins that reside in the various departments of the organization and the management systems create a seamless Digital Thread, capturing the lifecycle information of each personalized product. Personalized product is proposed to be developed through a self-organizing shopfloor, working on a multi-agent mechanism and controlled by a central agent control algorithm, which can coordinate and provide individualized process plans. The Digital Twins, interlinked by a Digital Thread and realized by a self-organizing shopfloor, thus result in increased level of automated control in engineering and manufacturing. To validate the feasibility of this proposed framework, we tested the information flow in the Digital Thread with a case study in the construction industry. Finally the challenges faced by such an automation framework and the area of future work are also discussed.

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Mass personalization is arriving. It requires smart manufacturing capabilities to responsively produce personalized products with dynamic batch sizes in a cost-effective way. However, current manufacturing system automation technologies are rigid and inflexible in response to ever-changing production demands and unforeseen internal system status. A manufacturing system is required to address these challenges with adaptive self-organization capabilities to achieve flexible, autonomous, and error-tolerant production. Within the context, the concept of Self-Organizing Manufacturing Network has been proposed to achieve mass personalization production. In this paper, we propose a four-layer system-level control architecture for Self-Organizing Manufacturing Network. This architecture has additional two layers (namely, Semantic Layer and Decision-Making Layer) on Physical Layer and Cyber Layer to improve communication, interaction, and distributed collaborative system automation. In this architecture, manufacturing resources are encapsulated as Semantic Twins to make interoperable peer communication in the manufacturing network. The interaction of Semantic Twins consolidates system status and manufacturing environment that enables multi-agent control technologies to optimize manufacturing operations and system performance.