Download PDF
Managing the Bullwhip Effect in Semiconductor Supply Chain: A Case Study of Infineon Technologies AG
Technology Category
- Functional Applications - Inventory Management Systems
- Infrastructure as a Service (IaaS) - Backup & Recovery
Applicable Industries
- Automotive
- Semiconductors
Applicable Functions
- Logistics & Transportation
- Warehouse & Inventory Management
Use Cases
- Demand Planning & Forecasting
- Supply Chain Visibility
Services
- System Integration
- Testing & Certification
The Challenge
Infineon Technologies AG, a global top 10 semiconductor company, faced significant challenges in managing the volatility in demand and the bullwhip effect in their supply chain, especially during the COVID-19 pandemic. The semiconductor industry is characterized by capital intensity and high demand volatility, which is highly dependent on innovation cycles. The bullwhip effect, a phenomenon where order fluctuations are amplified as they move up the supply chain, was a major concern for Infineon. During the pandemic, the demand for automotive semiconductors dropped significantly due to reduced commuting, leading to excess inventory. However, when the market rebounded, the increased demand coincided with a global computer microchip shortage, exacerbating the bullwhip effect.
The Customer
MCM (Machine Centers Manufacturing)
About The Customer
Infineon Technologies AG is one of the world's largest semiconductor manufacturers, with a workforce of over 50,280 people worldwide. In 2021, the company reported revenue of more than €11 billion. Following the acquisition of the US company Cypress Semiconductor Corporation in April 2020, Infineon became a global top 10 semiconductor company. The company operates in an industry characterized by high capital intensity and demand volatility, with demand being highly dependent on innovation cycles and prone to the bullwhip effect.
The Solution
To address these challenges, Infineon's supply chain engineers decided to apply system dynamics tools to study the bullwhip effect. They aimed to understand the impact of end-market scenarios on the bullwhip effect throughout the supply chain. The engineers identified end-market demand recovery scenarios, created a system dynamics supply chain model in AnyLogic, tested the model using historical data, and conducted a sensitivity analysis to identify parameters with the most significant impact on results. The supply chain model included four echelons: OEMs, Tier-1 supplier, Tier-2 supplier, and Semiconductor supplier. Each echelon was modeled to pass inputs through several control loops before outputting to the next stage. The model assumed that the semiconductor supplier reserves were infinite, guaranteed by the silicon supplier.
Operational Impact
Quantitative Benefit
Related Case Studies.
Case Study
Integral Plant Maintenance
Mercedes-Benz and his partner GAZ chose Siemens to be its maintenance partner at a new engine plant in Yaroslavl, Russia. The new plant offers a capacity to manufacture diesel engines for the Russian market, for locally produced Sprinter Classic. In addition to engines for the local market, the Yaroslavl plant will also produce spare parts. Mercedes-Benz Russia and his partner needed a service partner in order to ensure the operation of these lines in a maintenance partnership arrangement. The challenges included coordinating the entire maintenance management operation, in particular inspections, corrective and predictive maintenance activities, and the optimizing spare parts management. Siemens developed a customized maintenance solution that includes all electronic and mechanical maintenance activities (Integral Plant Maintenance).
Case Study
KINESYS Semiconductor Factory Automation Software
KINESYS Software provides both Integrated Device Manufacturer (IDM) and Original Equipment Manufacturer (OEM) customers world-class software products and solutions for advanced wafer and device traceability and process management. KINESYS offers state of the art database technology with a core focus on SEMI standards. KINESYS’ challenge was to make back-end processing failure-free and easy to use for clients while supporting licensing models more adaptable to changing industry needs.
Case Study
Monitoring of Pressure Pumps in Automotive Industry
A large German/American producer of auto parts uses high-pressure pumps to deburr machined parts as a part of its production and quality check process. They decided to monitor these pumps to make sure they work properly and that they can see any indications leading to a potential failure before it affects their process.