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Bosch - Wuxi - China Plant - Industry 4.0 Lighthouse Plant - Industrial Engineering 4.0

 


Tech & Sci 11:29, 19-Sep-2018

Wuxi factory embraces new technologies for smarter production

Updated 11:13, 22-Sep-2018

By Xu Mengqi, Ding Yi

https://news.cgtn.com/news/3d3d674d336b6a4d7a457a6333566d54/index.html


Illuminating the way

With Bosch’s manufacturing operation at Wuxi identified as a “Lighthouse” of industry 4.0, Mike Farish takes a closer look the site’s data-driven developments and explores a similar beacon of progress based in the UK

Mike Farish, Published 2 May 2019 

https://www.automotivemanufacturingsolutions.com/smart-factory/illuminating-the-way/525869




Bosch Automotive Diesel Systems (RBCD) plant in Wuxi in southern Jiangsu province, China


 Christophe Chapdelaine, senior vice-president manufacturing and quality management at the plant



In order to pilot Industry 4.0  approach the company decided to apply it first to machining, a key manufacturing procedure at the Wuxi site.

 “We use over a hundred 5-axis machining centres which are equipped with Bosch Rexroth MTX CNC systems,” 

“We deal with special steel as the raw material for our products and the main processes are high speed milling and drilling to high precision.”


Wuxi site set out on a six-month project to set up an industrial i4.0 framework integrating newly installed machine-condition sensors with individual cutting tool information.


“Bosch Nexeed PPM (Production Performance Manager) can be rolled out plant wide as a standard industrial i4.0 platform for predictive maintenance or real-time process and machine condition monitoring. It is compatible with standard industrial communication protocols like OPC-DA, which enable communication between machines and IT systems.”


“We installed Bosch Rexroth control to acquire data from motors and encoders with the parameters including torque, position and angle,”. 

“We also use MEMS (micro electro-mechanical system) sensors to gather vibration data.”



This set-up is aimed at gathering three distinct types of cutting tool information,: “The first is the tool pre-setting data, like tool length, radius and run-out. The second is tool life cycle, including tool grinding/re-sharpening batch, tool reached lifetime and tool change reasons. The third comprises data on tool inventory and location.”



appropriate analysis tools then turn this raw data into useful information to enhance manufacturing efficiencies. “We maximise tool life and minimise the tool quantity in circulation by using advanced data analytics,” he says. “All these help us to lower the tool inventory and cost and also provide relevant experts with powerful insights.”  These data gathering techniques have also been supplemented by the use RFID tags.



Data analysts with machining experts, together analyze data.  These different sets of expertise enabled the visualisation of the data and the development of customisable reports with increasingly powerful analyses, including diagnostic, predictive and prescriptive functions. In consequence plant personnel now have a deep understanding of cutting tool cost drivers, can identify tool types likely to sustain extended life quantities and are able to adjust inventory to future demand.



The reports  zero in on the causes of unnecessary expense. “We generate reports like Analyse and Diagnose Tool Premature Change Root Cause, Predict Tool Consumption and Prescription: Business Case Oriented Self-adjusting Tool Change Rule (cost vs. output…),” . “These customised reports combine the needs of domain experts and the recommendations of data experts and are created using a visual analytics platform, which is flexible, interactive and easily accessible by each user.”



By mid-2017 this approach had not only led to double-digit tool cost improvements but had also inspired the organisation to come forward with further big data applications including predictive maintenance and bottleneck analysis. Over the past two years during a critical high-demand situation these activities have further contributed to an increase in output of more than ten per cent in selected areas.


““Data analytics provides us with new methods and insights to improve quality, productivity and delivery,” 

Interesting Article - Mentions Wuxi - But a more general article

Dean CHEN Fangruo: Intelligent Manufacturing and Management Innovation

2024-01-22International Office

https://www.acem.sjtu.edu.cn/en/insight/81336.html



Global Lighthouse voices: A talk with Bosch Mobility China COO Norman Roth
April 18, 2025 | Interview






First, I believe in being nice to people but merciless to the process.

Another idea—and this in line with the thinking of Taiichi Ohno, founder of the Toyota production system—is to develop an “anger” against waste.


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Thanks to gen AI models, you can take a work instruction or a quality document in Chinese, and with one click, translate it into multiple languages generating content tailored to very specific inquiries.









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