The Smart Factory as an Adaptive Solution to the Challenges of Emerging Technologies
Founded in Milan in 1932, Mollificio Lombardo S.p.A. is a historical manufacturer of high-tech elastic components that meet the needs of the most important domestic and foreign market sectors. Renowned for precision and quality, its products are destined for the mechanical, electronics, textiles, aerospace, automotive, and communications industries, where international standards dictate strict technical and quality requirements. With the goal of meeting the needs of even the most demanding customers, Mollificio Lombardo continues to invest in technology and service development, with particular attention to people, who represent the driving force for the future.
The Context
Mollificio Lombardo has always paid attention to evolving production technologies, constantly upgrading both its machinery (especially bending machines) and production management IT systems (MES, ERP, etc.).
Following the introduction of European policies encouraging Industry 4.0 activities, the main machine suppliers began to provide connectivity systems for monitoring production parameters via proprietary or pseudo-standard protocols.
To further optimize production with an Industry 4.0 perspective, the company set out to complement its existing MES with a new system, one that could communicate with various protocols of machine suppliers and provide a simple graphical representation of the main production KPIs (OEE in particular).
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The Choice
The development of the project hinged on a seamless integration with the MES system already in use within the company, as well as with the protocols of various machine suppliers, so as to avoid disrupting production. By collaborating with Dedagroup Business Solutions, the company identified ThingWorx Manufacturing Apps and Kepware by PTC as the ideal technology.
Within just one week, the system was up and running, allowing production managers to accurately monitor activities and spot potential issues in real time.
Mollificio Lombardo then decided to expand the integration project to as many production machines as possible, enabling them to control an increasing number of production processes. Additionally, the data generated and stored by the new system can be leveraged to predict potential issues during production processes or improve maintenance planning.