US to tax on imported solar panels and washing machines
The products in question are specifically solar pa...
The US has announced that it will introduce import tariffs on certain foreign-manufactured products.
The products in question are specifically solar panels and washing machines, the trump Administration confirmed.
The tariff will be implemented through a Section 201 safeguard clause, due to imported products being “a substantial cause of serious injury to domestic manufacturers”, according to the US International Trade Commission.
Solar panels are to be taxed a 30% tariff during the first year of implementation, decline to 15% after four years.
However, the nation is able to import up to 2.5GW of unassembled solar panels without facing the tax.
The first 1.2mn imported washing machines will see a tariff of 20%, with the remaining facing a 50% tax.
In three years’ time these numbers will drop to 16% and 405 respectively.
“Our action today helps to create jobs in America for Americans. It will provide a strong incentive for LG and Samsung to follow through on their recent promises to build major manufacturing plants for washing machines right here in the United States,” said President Donald Trump.
“We support a resolution that is in the interest of American workers and, also, the American consumer. We’re going to benefit our consumers, and we’re going to create a lot of jobs.”
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.