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The emphasis of the journal Robotics and Computer-Integrated Manufacturing is on disseminating the application of research to the development of new or improved industrially-relevant robotics, manufacturing technologies, and innovative manufacturing strategies. Preference is given to papers describing original research that includes both theory and experimental validation. Comprehensive review papers on topical issues related to robotics and manufacturing will also be considered. Papers on conventional machining processes, modelling and simulation, supply chain management, and resource optimisation, will generally be considered out of scope, as there are other more appropriate journals in these areas. Overly theoretical or mathematical papers will be directed to other more appropriate journals as well. Original papers are welcomed in the areas of industrial robotics, humanrobot collaborative manufacturing, cloud-based manufacturing, cyber-physical production systems, big data analytics in manufacturing, smart mechatronics, machine learning, adaptive and sustainable manufacturing, and other fields involving unique manufacturing technologies.

Reconfigurable manufacturing systems (RMS) are considered the future of manufacturing, being able to overcome both dedicated (DMS) and flexible manufacturing systems (FMS). In fact, they provide significant cost and time reductions in the launch of new products, and in the integration of new manufacturing processes into existing systems. The goals of RMS design are the extension of the production variety, the adaption to rapid changes in the market demand, and the minimization of the investment costs. Despite the interest of many authors, the debate on RMS is still open due to the lack of practical applications. This work is a review of the state-of-the-art on the design of cellular RMS, compared to DMS, by means of optimization. The problem addressed belongs to the NP-Hard family of combinatorial problem. The focus is on non-exact meta-heuristic and artificial intelligence methods, since these have been proven to be effective and robust in solving complex manufacturing design problems. A wide investigation on the most recurrent techniques in DMS and RMS literature is performed at first. A critical analysis over these techniques is given in the end