MaxGrip developed a strategic blueprint for the maintenance processes of a renowned international beverage company. This blueprint is rolled out in a tailor–made deployment model to production locations worldwide. We reviewed and optimized all APM business processes, structured the new Maximo EAM system and during implementation train and coach the local teams at the production locations. Maintenance maturity is one of the highest priorities for this global FMCG company.
As with all companies operating on a global scale, one of the biggest challenges is internal alignment across sites and countries. In order to work in a uniform way and contribute to the same common goal, global business processes in line with the organization, systems, data and reports must be standardized. MaxGrip was asked to design a consolidated EAM blueprint that incorporates existing maintenance guidelines while deploying a new EAM system and optimizing standards.
Case study – highlights
Approach
The project started out with the design phase of the global EAM blueprint. Taking existing standards as the starting point, for each process a multidisciplinary team of subject matter experts prepared new process designs in various sessions. The deployment of the tailor-made maintenance blueprint is still under way. Factors for success: the standardized deployment approach, Fit/gap and Ramp Up.
Results
The project is under way with 36 production locations in 21 countries having been deployed. We will deploy at eleven more sites which will add eight more countries to the global project. We set and monitor performance against business critical KPIs and relate use of the EAM system to actual improvement of the plant’s Total Cost of Ownership. The global rollout of this uniform way of working enables the multinational to benchmark across sites.
Although the EAM blueprint and deployment project is not yet completed, so far, the beverage multinational shows an increased OEE with 1 – 2% and extended lifetimes of their assets. With some of the production facilities still to be deployed, those results are expected to improve further.
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In 2030, asset management will be reshaped by AI, emphasizing predictive maintenance. This evolution signifies a commitment to digital innovation and environmental consciousness, adapting to global technological trends for improved efficiency and sustainability.
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