Case: The SCORE methodology identifies the most effective changes
Evoma AB helps companies across multiple industries drive efficiency and support digital transformation through advanced technologies such as AI, simulation and data analytics. The company has developed three core pieces of software: a discrete event simulation platform, an optimisation platform, and a data analysis and data mining application.
Their flagship product, FACTS Analyzer, integrates these to offer predictive and AI-driven prescriptive analytics.Evoma is also working on energy saving solutions and reinforcement learning to improve decision-making and efficiency.
The challenge that needed solving
A manufacturing company faced a severe production bottleneck where customer demand exceeded supply capacity. With 50 production steps and constraints in cycle times, availability, downtime and changeover times, capacity was maxed out. Traditional methods such as trial-and-error and Lean processes could not solve the problem. The company needed a solution that could identify the right improvement actions to increase throughput.
Description of the solution and technology used
Evoma reformulated the problem into a multi-objective optimisation using its unique SCORE (Simulation-based Constraint Removal) methodology. Through simulation and optimisation, different improvement measures were analysed to identify the most effective changes. The simulations allowed combinations of improvements to be examined and ranked according to their impact on throughput, resulting in a clear action plan.
Results and success factors
The SCORE methodology identified seven critical improvement actions that, when implemented in the right order, led to a 50% increase in throughput. This improved the company's ability to meet demand and increased production efficiency by focusing on the right areas. The rate per hour metric increased significantly, which was a key success factor.
The impact of innovation on industry and society
This approach has the potential to revolutionise the manufacturing industry by offering a data-driven and more efficient method to identify and eliminate production bottlenecks.Companies can use simulation and optimisation to make better decisions, leading to increased productivity, reduced costs and improved resource utilisation. Socially, this contributes to sustainable growth through optimised energy use and reduced waste of resources.
Future prospects and opportunities for further development
Evoma has ambitious plans to further develop its products, such as FACTS Analyzer, with new features like 3D interfaces and modular architecture.The company is also exploring new technologies such as reinforcement learning and AI-powered digital twins to further optimise production and resource use.
The aim is to broaden its offer to new industries and application areas, especially in energy optimisation and sustainable solutions.
Challenges during the development process and lessons learnt
Evoma has faced challenges in managing complex production systems while maintaining the user-friendliness of its solutions. By working closely with customers and partners, the company has been able to refine its technologies and ensure that they create real business value. Making tools easy to use without compromising on functionality has been a key learning point, allowing their solutions to successfully improve efficiency and sustainability in industry.
