Cerler Global Electronics relies on MAVAL to digitalise production planning
Cerler Global Electronics, a company specialised in the industrialisation and manufacturing of electronic products, will deploy Opcenter APS (formerly known as Preactor) with the goal of improving its ability to manage daily demand and enhance the capabilities of its shop-floor team. For this project, the company has chosen MAVAL as its technology partner to support its journey towards the smart factory by adopting Siemens’ Advanced Planning and Scheduling solution.
The company, with 30 years of history, is headquartered in La Muela (Zaragoza) and employs 350 people. In its 10,000 m² production area, it manufactures—under strict quality policies—900,000 components per hour for strategic sectors such as automotive, renewable energy, medical technology and home appliances.
Managing daily demand and skills
To reach the millions of parts produced each day, Cerler Global Electronics receives highly varied orders in terms of frequency, lead times and quantities. For this reason, the planning team sees it as strategic to deploy a solution such as Opcenter APS (Preactor) to adjust plans quickly and reliably, considering at all times availability (stock, materials, etc.) and delivery times to uphold its quality commitment—not only in production but also in service. Planning changes will no longer be an obstacle to daily demand management, which will adapt in an agile and intelligent way, moving from weekly replanning to the possibility of doing it daily.
Likewise, Opcenter APS will enable the company to manage the skills of plant technicians and adjust the production calendar and expert staffing per product or machine, so that these skills are expressed at their best in production and, therefore, reflected in the quality policy that governs the company’s day-to-day operations.
Manuel Morón, Cerler’s Plant Director, states: “With Opcenter APS we expect to take a qualitative leap in our planning and sequencing tools, enabling us to be much faster and more efficient in the decision-making required by a highly variable demand and context.”