Blockchain Production Planning in Mass Personalized Environments

Abstract

Industry 4.0 has substantially increased the degree of coordination and autonomy of production systems, lending manufacturing systems the ability to respond flexibly to the changing conditions of the market. Additive technologies enhance still further the flexibility of production processes. This increasing flexibility will allow the implementation of business strategies oriented towards satisfying “long tail” demands (mass customization and mass personalization). This poses the question of how to manage efficiently the production of goods that incorporate intangibles, like the preferences of individual customers. This is a novel problem in the field of Service Operations Management (SOM), namely the design of a management system able to elaborate in the aforementioned autonomous and decentralized way the production plans in mass customized/personalized environments in which the goods are individual requests incorporated in physical objects. This system, which draws on the capacities of cyber-physical systems (CPS), will be able to generate individual prototypes based on the specification of customers and, if it responds to their demands, plan the operations for its fabrication. The result will be a data structure autonomously elaborated by the network of CPS. This database must be freely available to all the CPS involved in the production process. This large data structure can be configured as a blockchain. That is, the intervening CPS will sequentially generate the blocks codifying the information needed to elaborate a production plan for a customized/personalized good. This structure will allow the intervention of “expert CPSs” at each step, signing their contributions as well as the hashing of the previous blocks. The use of Big Data methods will provide the grounds for applying Proof-of-Stake tests that will disallow revisiting the previous stages and will induce a chain of blocks capturing, in the end, the entire plan. The blueprint for this architecture is our original contribution to the SOM literature.