Michael Teucke
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View article: Autonomous Control of Logistic Processes: A Retrospective
Autonomous Control of Logistic Processes: A Retrospective Open
Manufacturing and logistic service companies are increasingly confronted with high dynamics and complexity. Due to its particular suitability for short-term and situation-dependent decision-making, autonomous control can improve planning a…
View article: Automobile Logistics 4.0: Advances Through Digitalization
Automobile Logistics 4.0: Advances Through Digitalization Open
In today’s buyer’s markets, logistical service quality is of great importance, particularly for high-priced products. For many buyers, the automobile is the epitome of a high-priced, individually customized product. Hence, customers expect…
View article: Recognition of car parts in automotive supply chains by combining synthetically generated training data with classical and deep learning based image processing
Recognition of car parts in automotive supply chains by combining synthetically generated training data with classical and deep learning based image processing Open
In the automotive industry, the "completely knocked down" (CKD) business requires the identification and verification of a large number of unmarked parts. This is often a manual activity with a high risk of failure. Deep learning methods o…
View article: Deep Learning-based Object Recognition for Counting Car Components to Support Handling and Packing Processes in Automotive Supply Chains
Deep Learning-based Object Recognition for Counting Car Components to Support Handling and Packing Processes in Automotive Supply Chains Open
Complex distributed supply chains, e.g., in the automotive industry, need to cope with high product variety. Digital image processing can use specific geometric and optical properties of parts and components for determining their type and …
View article: Travel Time Prediction in a Multimodal Freight Transport Relation Using Machine Learning Algorithms
Travel Time Prediction in a Multimodal Freight Transport Relation Using Machine Learning Algorithms Open
Accurate travel time prediction is of high value for freight transports, as it allows supply chain participants to increase their logistics quality and efficiency. It requires both sufficient input data, which can be generated, e.g., by mo…
View article: Using Sensor-Based Quality Data in Automotive Supply Chains
Using Sensor-Based Quality Data in Automotive Supply Chains Open
In many current supply chains, transport processes are not yet being monitored concerning how they influence product quality. Sensor technologies combined with telematics and digital services allow for collecting environmental data to supe…
View article: Identification of Sensor Requirements for a Quality Data-based Risk Management in Multimodal Supply Chains
Identification of Sensor Requirements for a Quality Data-based Risk Management in Multimodal Supply Chains Open
Rising volatility in globally distributed supply networks leads to an increasing need of supply chain event management. Event-driven control requires sensor-based, real-time quality data. The article presents necessary capabilities of sens…
View article: Sharing Sensor Based Quality Data in Automotive Supply Chain Processes
Sharing Sensor Based Quality Data in Automotive Supply Chain Processes Open
In current supply chains (SC), many process steps are not yet being monitored for proper quality. Adding product and process quality supervision can improve supply chain performance by reducing production loss and emergency transports. Due…