Meccanica del sarca

The project aims to automate the quality process of production lines, carried out until now manually, to improve it by monitoring defects and correcting any drifts.

company name

Meccanica del sarca

project title

Optimage Cooperation

size and location

Grande impresa, Trento


Politecnico di Milano (Dipartimento di Meccanica, Dipartimento di Elettronica, Informazione e Bioingegneria)

Politecnico di Milano

Competencies used

Quality 4.0

The problem

Meccanica del Sarca has installed production lines of loader tanks in which the quality level is based on a phase of aesthetic and dimensional that is still manually carried out by the staff, using gauges specifically designed and build for each type of tank. These operations, completely manual, aim to identify any non-conformities a the beginning of the welding process, heat treatment of case-hardening, and tempering after which it is possible to find geometrical distortions that can affect the dimensional characteristics of the piece up to compromising its functionality. 

The quality control process of the production lines of loader tanks (Beretta, ed.), aimed at verifying the aesthetic and dimensional conformity, is still manually carried out by the staff. 

  • Operators carry out repetitive activities with low added value (each operator inserts each magazine in a special gauge, they check if it has the same size, and if not, they apply a plastic deformation to conform it).  

  • There is a problem of quality control reliability, which is the responsibility of the operator. 

  • Time necessary to perform quality control has a relevant impact on the production cycle. 

  • Only quality operators have the skill to carry out a check. 



  1. Artificial intelligence and deep learning are used for automated identification of non-conformities in production (defects). 

  2. Sensors: optical sensors analyze the component profile to determine if it conforms to design specifications. 


There is an internal impact to the company, that can strengthen its quality control: 

  • by monitoring defects; 

  • By correcting any drifts of the production process. 

The operator will not have to carry out a repetitive task, that now he is obliged to control manually, through automation of the component measuring station. 

Thanks to an AI algorithm to control the quality, the company gains knowledge about any defects of its components. Then, it becomes independent of operators’ ability to assess the defects. It enhances decisions making ability and autonomy.

Benefits for the company

  • Automatically identify the conformity/non- conformity of a tank. 

  • Automatically indicate any repair possibility for non-conforming products. 

  • Indicate repair activities for repairable products. 

  • Have a system able to automatically learn knowledge based on the operator’s alternative choices  

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