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Introduction

Meccanica del Sarca specializes in the mechanical processing of walnut wood for the production of rifle stocks, forends, and magazines.

The problem

With the aim of expanding its workspace, Meccanica del Sarca has planned the physical separation of two production areas: one dedicated to mechanical machining for chip removal, and the other dedicated to the painting of semi-finished wood products. This configuration, which aims to optimize production space in order to meet increased market demand, introduces a degree of complexity in terms of internal logistics: the two warehouses will be located approximately 100 meters apart.

This entails, first of all, a complication in terms of handling, as an external route in a complex environment (slopes, mud, ice) is required. Furthermore, considering the increase in production resulting from the improved efficiency of the production site and the need to move the trucks manually, this choice would entail an increase in dedicated resources with a consequent impact in terms of unproductive costs.

The solution

The solution, in line with lean production principles aimed at minimizing unproductive costs and activities with no added value, involved a feasibility study for the design of an AGV prototype capable of delivering materials precisely to the area where they are needed in the production cycle, communicating with other actors involved in the production cycle (machines, people, information systems) and overcome physical obstacles such as non-industrial flooring or atmospheric agents typical of the Alpine climate characteristic of Trentino (snow, ice, wind, etc.).

Technologies

Development of a prototype AGV (Augmented Guided Vehicle) capable of operating reliably both indoors and outdoors. The logistics modules must be able to travel at least 80-90 meters in open terrain in all weather conditions and approximately 40-50 meters inside buildings.

Artificial Intelligence capable of enabling the AGV to cover different routes in close proximity to people, vehicles in transit, and any obstacles that may be present on the route (parked vehicles, temporary material deposits, etc.); fleet management algorithms will be used to activate alternative route strategies in order to complete the mission in all conditions.

IoT and Machine2Machine (M2M) solutions are necessary to enable the AGV control system to monitor the route and open/close access gates to buildings in the right way and at the right time to ensure the mission is completed. In addition, a set of sensors will be introduced that are capable of detecting not only the presence of obstacles, both stationary and moving, but also of assessing external weather conditions (temperature, rain, snow, ice). This provides the artificial intelligence system with all the information it needs to plan different mission strategies, with the aim of completing the mission at all times.

Desired impacts

Identification of a mechanical solution capable of providing an AGV with traction capacity exceeding market standards, taking into account both environmental characteristics and the condition of the route. The solution must be able to withstand the presence of rainwater, even in large quantities, and cold temperatures.

The identification of a system equipped with sensors, an M2M communication protocol, and artificial intelligence algorithms that guarantees the possibility of automatically integrating the internal logistics process, eliminating the use of human resources for manual inbound logistics activities, thus allowing them to be dedicated to activities with greater added value.

Benefits for the company

Streamlining of the logistics process: the implementation of intelligent AGVs with sufficient traction capacity to eliminate low value-added manual activities.

Expansion of production capacity: Meccanica del Sarca’s industrial plan anticipates an increase in demand, which can only be met through the introduction of intelligent solutions to support skilled operators.

Integration of operational processes: the AGV fleet, as designed, will involve the full integration of the information systems involved in the production process, such as ERP (for order management), MES (for production progress control), the production facility access system, and the fleet control system.