With the development of Industry 4.0 and cloud computing technology, personalized customization as a new production mode is showing a trend of rapid development. Personalized customization has the characteristics of order-driven production, strict processing times, high dynamic external conditions, and large flexibility in the production process, all of which bring more uncertainty to the production system and great challenges to the edge computing processing of related tasks in personalized customization production. Aiming at the above problems, a thing-edge-cloud collaborative computing decision-making (TCCD) method in customized production is proposed. First, the architecture of a personalized customized production system used for implementing the TCCD method is presented. Then, according to the number and type of products in the customer order received from the private cloud platform, the customer’s personalized customized order is dynamically divided. Subsequently, a task priority sorting algorithm is proposed to optimize the waiting time of all tasks involved in the order. Furthermore, a discrete particle swarm algorithm is proposed to optimize the average execution time of all tasks and equipment utilization decision-making options (thing-edge collaborative computing, edge-edge collaborative computing, or edge-cloud collaborative computing). Finally, the effectiveness of the proposed TCCD method is verified by using the prototype platform of personalized product packaging intelligent production line with the same process flow.