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Ansaldo Energia Enhances Data Quality and Monitors Production KPIs with Automated Analytics
Technology Category
- Functional Applications - Manufacturing Execution Systems (MES)
- Platform as a Service (PaaS) - Data Management Platforms
Applicable Industries
- Buildings
- Cement
Applicable Functions
- Logistics & Transportation
- Quality Assurance
Use Cases
- Additive Manufacturing
- Visual Quality Detection
Services
- Testing & Certification
The Challenge
Ansaldo Energia, a nearly 200-year-old company manufacturing generators and turbines for thermoelectric power plants in over 90 countries, faced a significant challenge with data quality. The company's main source of resource planning data, SAP, was being polluted with inaccurate data from various departments, negatively impacting the supply chain. This inaccurate data often led to incorrect orders, disrupting the manufacturing schedule and the planning department’s budget. Guglielmo Mantero and his team at Ansaldo Energia were tasked with creating a set of KPIs to ensure the accuracy of their ERP and SCP data. However, they needed a new method to monitor these KPIs, focusing on data quality and the real impact of inaccurate or outdated information on Ansaldo Energia’s manufacturing processes.
About The Customer
Ansaldo Energia is a long-standing company that has been in operation for nearly 200 years. The company specializes in manufacturing generators and turbines for thermoelectric power plants and serves more than 90 countries worldwide. This requires intricate planning of projects and resources to ensure that customers receive their equipment and components on time and perfectly manufactured. Ansaldo Energia uses SAP as its main source of resource planning data, with various departments and teams inputting data into the system. Guglielmo Mantero, a master planner at the company, works closely with the company’s schedulers, building out short- and long-term strategies for Ansaldo Energia’s manufacturing lines and ensuring the supply chain can support the company’s requirements.
The Solution
The solution came in the form of Alteryx, a data analytics tool. Mantero, after being informed of an Alteryx trial within the company, started experimenting with Alteryx Designer. He built workflows that could take data from SAP, match the data against other data sets, and output it as a spreadsheet for more hands-on analysis. Mantero used Alteryx Designer to create workflows for two KPIs: one that tracks planned and released orders for components and materials, and another which monitors when those items are withdrawn for use in a project. The use of Alteryx Designer was not limited to the planning department. Colleagues across supply chain, administration, and finance also started working with Alteryx to accelerate analytics and improve the quality of insights they were providing to leadership.
Operational Impact
Quantitative Benefit
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