The problem

Supply chain management used to be ineffective due to inconsistent data often taken under different, untimely criteria. Operators did not have access to the company knowledge base to solve specific problems and it was difficult to contact appropriate experts. The Business Intelligence & Analytics group, responsible for supply chain performance, was unable to optimize production due to a lack of end-to-end visibility for the entire process. Furthermore, inefficient internal communication had negative impacts on production planning and management interference in the event of problems.

The solution

With Keethings, a solution was implemented that allowed for immediate collection and propagation of information within the plant. The company managed to speed up and facilitate communication not only among operators but also with the senior management team responsible for production. Keethings additionally made the distribution of standardized reports and problem-solving guides easier. The integration of Keethings with production lines allowed for the automatic collection of machine alerts, managing them through predefined workflows and thus reducing problem lead times. The availability of more consistent, updated data has also resulted in more accurate analyses of the production process, and the identification of areas for improvement.


The result

The benefits of using Keethings are numerous. First, it enables you to work with accurate data. This means greater end-to-end visibility for the production value chain and better production planning. Streamlining alert management and escalation processes had an extremely positive impact on response times in cases of halts or malfunctions. Eventually, the operator could solve most problems autonomously by consulting the company's knowledge base and collaborating with the domain expert in real time. But these are only the most immediate and measurable benefits. Adopting Keethings meant making all necessary data available to the workforce, translating into more proactive and less reactive work methods. Finally, the future is open to exciting uses of the collected information to create predictive maintenance models.

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