Addressing the Scalability Bottleneck of Semantic Technologies at Bosch

09/19/2023
by   Diego Rincon-Yanez, et al.
0

At the heart of smart manufacturing is real-time semi-automatic decision-making. Such decisions are vital for optimizing production lines, e.g., reducing resource consumption, improving the quality of discrete manufacturing operations, and optimizing the actual products, e.g., optimizing the sampling rate for measuring product dimensions during production. Such decision-making relies on massive industrial data thus posing a real-time processing bottleneck.

READ FULL TEXT
research
08/29/2020

AI-based Modeling and Data-driven Evaluation for Smart Manufacturing Processes

Smart Manufacturing refers to optimization techniques that are implement...
research
05/22/2022

Positioning Fog Computing for Smart Manufacturing

We study machine learning systems for real-time industrial quality contr...
research
05/16/2022

Analysis of Distributed Ledger Technologies for Industrial Manufacturing

In recent years, industrial manufacturing has undergone massive technolo...
research
01/17/2022

Process Visualization of Manufacturing Execution System (MES) Data

Process visualizations of data from manufacturing execution systems (MES...
research
07/08/2020

Strategic Evaluation in Optimizing the Internal Supply Chain Using TOPSIS: Evidence In A Coil Winding Machine Manufacturer

Most of the manufacturing firm aims to optimize their Supply Chain in te...
research
11/25/2021

Ontology-Based Skill Description Learning for Flexible Production Systems

The increasing importance of resource-efficient production entails that ...
research
06/02/2021

Decision-making Oriented Clustering: Application to Pricing and Power Consumption Scheduling

Data clustering is an instrumental tool in the area of energy resource m...

Please sign up or login with your details

Forgot password? Click here to reset