Addressing the Scalability Bottleneck of Semantic Technologies at Bosch

TL;DR

This paper discusses the challenge of real-time processing bottlenecks in semantic technologies used for smart manufacturing, emphasizing the need for scalable solutions to handle massive industrial data for decision-making.

Contribution

The paper identifies scalability issues in semantic technologies within industrial settings and proposes approaches to overcome these bottlenecks for real-time decision-making.

Findings

Identified key scalability bottlenecks in semantic processing

Proposed methods to improve real-time data handling

Enhanced decision-making efficiency in manufacturing

Abstract

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.