Anarchic Manufacturing Systems

Lead Research Organisation: University of Bristol
Department Name: Mechanical Engineering


The proposed research area is a novel and alternative system to schedule and manage smart factories. Current scheduling and management methods are traditionally hierarchical and centralized, but are known to be inflexible and unable to embrace complexity resulting in suboptimal and inefficient realworld operations. This is compounded for highly volatile and dynamic environments. Using Industry 4.0 enabling technologies, such as Internet of Things and autonomous robotics, the Anarchic Manufacturing System aims to solve the scheduling problem by providing the smart factory with a completely distributed heterarchical decision making structure, where decision making authority and autonomy is at the lowest level between system elements (e.g. machines, products, resources). Two major hypothesizes to be explored are; distributed anarchic manufacturing systems are more flexible and potentially self-healing in volatile environments, and they can embrace complexity and operate more efficiently in dynamic scenarios than hierarchical systems.
To conduct the research I intend to predominately use simulation modelling techniques; notably Agent Based modelling, AnyLogic is a suitable existing multi-method modelling platform that I have had prior experience with whilst researching this same topic during my Masters. Simulation modelling should provide majority of the necessary tools to evaluate the Anarchic Manufacturing System, but if possible and during later stages, a physical demonstrator may be suitable to show case the technology and validate methodologies and simulation models. A physical demonstrator can be small lab based programmable robots to do simple tasks from decision making and situational awareness, it can alternatively use a real manufacturing system that is flexible and intelligent enough if the opportunity arises.


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publication icon
Ma A (2018) Anarchic manufacturing in International Journal of Production Research

Studentship Projects

Project Reference Relationship Related To Start End Student Name
EP/N509619/1 01/10/2016 30/09/2021
2013887 Studentship EP/N509619/1 01/02/2018 31/07/2021 Andrew Ma
Description Anarchic manufacturing has been created, a distributed production planning and control system for manufacturing. Through agent based simulations it was found that the distributed system can be applied to a wide range of scenarios, including assembly and product transition.
Exploitation Route The basis of anarchic manufacturing can be replicated for further study, additionally the novel application to advanced manufacturing scenarios can provide insight to others in how to tackle these problems with distributed systems.
Sectors Manufacturing, including Industrial Biotechology