Experiment name: COMPLEMANT

Manufacturing end-user: Ghepi Srl

The Business Sector

Ghepi operates in the plastic materials field with focus on injection molding technology.

The market is very wide and includes finished products, semi-finished products and components, cosmetic or technical, for many different applications: automotive, railway, mechatronics, electric and electronic, household appliances, barcode readers, logistics handhelds, automatic packaging machines, food and beverage packaging, medical devices, mechanical components, handling technologies, gardening equipment, fluid power, pumps, etc.

The Company

Ghepi Srl has been operating in the plastic material field since 1972 and deals with Project Development and Management, through a specific focus on partnerships with Customers.

It offers complete and on-demand solutions thanks to the capability to manage all the phases of a project, including consultancy on polymers to 3D design, CFD and FEM Analysis, mold construction (Italy, China, Portugal) and manufacturing. Ghepi Srl has 25 injection molding machines, supported by few skilled operators, manipulators and cobots, based on different technologies: Injection molding, Gas-injection, Two-shot injection, In-mold decoration, Ultrasonic and Vibration Welding, Pad Printing, etc.

Ghepi is highly specialized in Metal Replacement with high performance polymers, with experience gained in co-designing with Customers and Suppliers.


The Challenge

As of today, Ghepi Srl has different injection moulding stations, where different components are produced. Between these, there is the station dedicated to conveyor handling components. The component injection moulding is completely automated but still requires on-board machine processing for the finishing process. A human operator is assigned to. The production pace is dictated by the cycle time of the moulding press (45 seconds) and forces the operator to work under an external, and very fast, pace determinant with consequent effects on the cognitive demand and on the quality of the output. Moreover, the worker is in charge of two relevant tasks, magnets insertion and quality control. For this reason, worker’s physical and mental stress have a relevant impact on production process’ performances and product quality.

Within this use-case, the key challenges identified by Ghepi Srl are:

  • Improve job satisfaction by establishing a system that continuously monitors operator’s working conditions and promotes improvement actions that tackle high physical or cognitive burden and reduce risky situations.
  • Reduce the appearance of mental stress conditions by evening out the peaks in cognitive demand through the combined effect of production system adaptation to static and dynamic operators’ characteristics and of cobot support in task execution.
  • Improve quality and economic sustainability of the process through the combined effect of automation support and organizational interventions.


Planned solution

The demo aims at deploying the mutualism concept in next-generation (worker-wise) customized and continuously adaptive work environments, where humans and machines complement their capacities in order to achieve optimized manufacturing performances and unprecedented worker satisfaction. This is achieved by streamlining the introduction of a new cobot in a SME working environment and by dynamically adapting its behavior to real-timely monitored physical and cognitive conditions of the operator.

The use of the cobot, introduced by the COMPLEMANT experiment in the to-be scenario is foreseen for supporting the operator in the different tasks of the process. The cobot’s introduction aims at not only increasing efficiency and quality, but as a well-being measure for the operator. The COMPLEMANT experiment continuously monitors both physiological and psychological worker parameters and couples them with context information to detect misalignments potentially ascribable to high cognitive or physical demands and possibly leading to reduced workers’ well-being and safety and/or system performances.

Different production system configurations, characterized by variable assignment of process’s tasks to operator and cobot, allow to make real-time interventions whenever operator and system behaviour deviates from optimal and safe performance. Cobot capabilities become an extension of those held by the worker and are modulated in order to cope with the worker’s specific characteristics, such as skills, physical and intellectual capacities and status (e.g. mental stress, loss of attention and fatigue), and with the system conditions that is currently being experienced.

COMPLEMANT strengthens dynamic adaptation of a cobot in selected tasks carried out within an injection moulding line. This will be achieved through a light infrastructure built over the HORSE framework organized into three logical steps:

  • Know the punctual status of the working environment through a Sensing Layer;
  • Analyse the gathered data;
  • React proposing interventions.

The COMPLEMANT experiment will leverage on the HORSE framework architecture and on the developed components to provide its functionalities.


Logo Website link
COMPLEMANT_ghepi http://www.ghepi.it
COMPLEMANT_holonix http://www.holonix.it
COMPLEMANT_supsi http://www.supsi.ch
COMPLEMANT_unimore http://www.unimore.it