Scientific objectives | Circular - Université Grenoble Alpes

For this project, we formulated different hypothesis and research challenges linked to the agility needed to achieving remanufacturing-based circular production systems at a significant scale.

First hypothesis

The agility of the remanufacturing system will result from the active collaboration of humans and robots/numerical systems for decision makings and executive tasks.

The workers and/or the work collectives will be key elements to realise the diagnosis, to make decision on the right process to put in place but also on the way to reorganise the agile industrial chain. Having this in mind is necessary to determine:

Who will be this (or these) “super worker(s)”, able to manage simultaneously the executive tasks and to adapt the organisation of the industrial process? Which new skills and which apprenticeships are necessary at the individuals and collectives levels for a better performance of those agile de-re/manufacturing systems.
What could be the information and/or expert system that will continuously assist the diagnosis of the workers or work collectives to make decisions along the remanufacturing chains?
How to make easier the programming of cobots to favor the use of cobotic at the cell level where the tasks will differ a lot and would be difficult to plan.

Quick and reliable adaptation and reconfiguration of the operative processes and work environments will be necessary for the agility of the de-re-manufacturing system. That reconfiguration would be driven by different information coming from the whole system and will be continuously or frequently analysed, using new available numerical technologies. It is then necessary to define:

What would be the design approach for the new products, considering that each product will be fitted to the customers’ needs but will also be related to numerous negotiations appearing all along its treatment?
How to help the definition of the system level of automation for the remanufacturing line (e.g. to find the suitable balance between operator and machine work) depending on the inputs and outputs of the line?
What will be safe working environments in a reconfigurable working place shared by humans and robots?
How to predict the future product lifetime to provide decision support for the productive system, considering both the state of health, but also using models fed by data collected or measured on the product itself?

Second hypothesis

Promoting de-re-manufacturing systems needs both to secure and incite their implementation conditions.

What will be the institutional conditions, including rules, economic incentives, human resources, employment and training, to develop de-re-manufacturing systems in the circular economy?
Who will be the actors, dependencies and externalities in new organisation and ways to deal with them?
How to help the design and dimensioning of the new supply chains involving those new actors.