Shanghai government to focus on green manufacturing
The nation has committed to having 1...
According to government officials, Shanghai will prioritise the promotion of its green manufacturing developments.
The nation has committed to having 100 green factories, 20 green industrial parks, and 10 green supply chains by 2020.
In addition to the new facilities, the municipality aims to create a structure for green manufacturing standards and assessments by the same deadline.
Green manufacturing relates to the production of items – from design and packaging, to application and recycling – that create little to no environmental damage.
The government also aims to target the use of energy within it’s manufacturing industry to clean up the process.
The announcement was made by officials on 5 June, in preparation for the launch of the Shanghai Energy-Saving Publicity Week, which will commence 11 June.
China has drawn a lot of focus on tackling its issues with air pollution, with aims develop green industries as key strategy.
Shanghai, however, has seen a rise in PM 2.5 particulate matter in its air of 1.9% year-on-year in the first quarter of 2018, despite nation-wide campaigns that tried to prevent this.
Predictive Monitoring for Continuous Operations Management
Unplanned downtime and poor maintenance procedure can cost companies a lot of time and money.
For companies looking to set specific targets for cost efficiency, production output and quality control, the ability to predict how certain variables affect machines can aid success in reaching these targets.
Monitoring and remediation are important steps to optimize production, by adopting Predictive Monitoring, organizations can receive the ideal support to keep operations running efficiently, and ongoing maintenance to keep machines running at their best.
Predictive Monitoring is an AI driven method of production analysis. It uses metrics such as temperature and vibrations to determine when machines are working outside of their optimum conditions.
Around 98% of organizations report that a single hour of downtime can cost them over US$100,000, which highlights a significant cost implication that can be avoided with AI driven analytics.
TwinThread applications work with Predictive Monitoring to provide a network of data, which ensure machines work within their optimum conditions, for the best output.
Providing the Digital Tools
According to PwC’s ‘Digital Factories 2020’ report, “manufacturers’ adoption of machine learning and analytics to improve predictive maintenance will increase by 38% by 2022.” One of the main reasons for this, given by 98% of respondents, is to gain more efficiency through investment into digital factory solutions.
By learning what potential issues may occur if machines are not working to the correct standard, Predictive Monitoring systems work with TwinThread’s Predictive Asset Reliability application, which conducts an “automated root cause analysis” enabling the operator to analyze how the machine has fallen from its optimum conditions. Ultimately, any issues will be addressed much faster when predictive technology uses data to monitor variables.
“TwinThread’s Predictive Operations Center is making a big difference to our process engineers, giving them real-time feedback on the stability of our production,” said Domenic Verte, Manufacturing Application Manager at Toray.