Big Data-Powered Tuning for Fast and Secure Processes
Company Size
1,000+
Region
- America
- Asia
- Europe
Country
- China
- Germany
- Mexico
- United States
Product
- Celonis Process Mining
- SAP
Tech Stack
- Process Mining
- SQL Database
- ERP System
Implementation Scale
- Enterprise-wide Deployment
Impact Metrics
- Cost Savings
- Customer Satisfaction
- Digital Expertise
- Productivity Improvements
Technology Category
- Analytics & Modeling - Big Data Analytics
- Application Infrastructure & Middleware - Data Exchange & Integration
- Functional Applications - Manufacturing Execution Systems (MES)
Applicable Industries
- Automotive
Applicable Functions
- Procurement
- Quality Assurance
Use Cases
- Inventory Management
- Predictive Maintenance
- Process Control & Optimization
- Supply Chain Visibility
Services
- Data Science Services
- Software Design & Engineering Services
- System Integration
About The Customer
Eissmann Automotive is a globally active family business founded in 1964, headquartered in Bad Urach, Germany. The company is the world’s leading manufacturer of high-quality shifter modules, trim components, and complete car interiors. With more than 5,000 employees across 13 production sites in Hungary, the Czech Republic, Slovakia, the US, Mexico, and China, Eissmann Automotive collaborates with nearly all renowned manufacturers in the automotive industry. The company combines traditional craftsmanship with state-of-the-art production processes to deliver high-quality products. Eissmann Automotive has digitized its entire process chain to ensure effective and profitable production, particularly for safety-related products such as driver airbags.
The Challenge
Eissmann Automotive faced the challenge of maintaining high-quality production standards while ensuring complete traceability and efficiency in their complex production processes. The company needed to digitize its entire process chain to monitor every production step, especially for safety-related products like driver airbags. Manual data evaluation methods were prone to errors, and there was a lack of transparency and traceability in the purchasing process. Additionally, the company needed to optimize its master data management to support various business processes effectively.
The Solution
Eissmann Automotive implemented Celonis Process Mining technology to monitor and optimize various business processes, including Purchase-to-Pay (P2P), Master Data Management (MDM), production, manufacturing management, and purchasing. The technology enabled the company to track and visualize the production cycle in real-time, identify bottlenecks, and uncover optimization potential. By connecting the Manufacturing Execution System (MES) to an AS-400 or SQL database, data from production processes were transmitted to the Celonis software for real-time tracking and analysis. This allowed Eissmann Automotive to achieve complete traceability, unify data evaluation, and make informed decisions to improve production efficiency. Additionally, Celonis Process Mining was used in master data management to ensure accurate and timely data availability, leading to significant process improvements and reduced throughput times. In purchasing, the technology provided transparency and traceability, enabling better supplier management and strategic purchasing decisions.
Operational Impact
Quantitative Benefit
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