Remanufacturing is a production practice that requires the work of producers, consumers, and the government. There are benefits associated with this production model, such as improving the environment, opportunities for cost savings, and others. However, it is essential to identify the factors that affect the possibility of acceptance of this production model. This research proposes a model based on different analysis methodologies and techniques of SEM (Structural Equations Modeling) and the method of PLS (Partial Least Squares). A total of 403 responses to the survey were collected from 1 November 2021 to 15 January 2022. For the data treatment, SPSS, Excel, and WarpPLS software were used to identify the variables, factors, and their direct and indirect effects among the latent variables, referring to a scheme focused on consumer perception based on the acquisition remanufactured products. This created model served as a reference to create and develop a design and repair strategy for White goods or similar products in handling, logistics, and repair. This design strategy was transformed into a business model based on a circular economy, particularly on a Product–Service System with social, economic, and environmental benefits for producers and consumers.

Design of Experiments as a subfield of statistics has its origins trying to understand systems and making decisions. In the context of food supply chains where agricultural and farm systems, packaging and processing plants, cold chains and food logistics, product design, warehousing, retailing, among many other steps and actors, come together to produce safe, healthy, nutritious, reliable, affordable, and sustainable food products. At each stage, many problems have to be solved and decisions have to be made from agricultural practices, scheduling, land use, costing, and pricing, at the farm and orchard level. A general outline is presented on the general workflow; illustrated through examples and a current review of some of the applications of design of experiments in the context of food production help provide some directives and guidelines. Global trends and challenges that influence both the food industry and the practice of design of experiments are discussed.