How to keep the wheels running – Could predictive maintenance add value to Your business?
Published March 16th, 2022
In today’s blog post, APL Systems Vice President Tapio Rintala and Risk Management Consultant Kari Muhli discuss predictive maintenance, process optimization and risk evaluation. Tapio has over 20 years of experience from Production Management. Kari is a leading Enterprise Risk Management Professional with extensive experience from multiple industries.
The benefit of evaluating risks of production stoppage
Mr. Kari Muhli on why it is important to evaluate the risks of stoppage: “A company needs to be aware of their typical maintenance indicators and different cost factors in case of production stoppage. It is important to know what kind of impact a production downtime can have to company’s business and evaluate the total costs of stoppage.
In addition to risks such as financial losses of unexpected production stoppage or negative impact to CO2 emissions, a stoppage can also influence customer satisfaction and service capability. Delivery delays may lead to financial sanctions and additional discounts given to customers. Finally, the poor results, in extreme cases, may lead to the loss of an important customer and severely harm your business. So, there are many issues that may arise from a breakdown of a single key component or machine.”
Predictive maintenance & predictive data
Typically, factories have a lot of equipment that are critical to the production process. Sometimes, traditional maintenance methods like preventive maintenance are not enough to keep everything in operation. This challenge can be tackled with predictive data.
APL Systems Vice President Tapio Rintala comments on the importance of predictivity: “Predictive information and acoustic data allows to optimize process cycles, minimize unplanned stoppages, or optimize production processes. One of the biggest benefits of predictive data is that you are always aware of the real situation and can plan and schedule important tasks ahead. Predictive maintenance utilized with real-time information about the condition of machinery reduces the amount of downtime to minimum possible and allows this workforce to be utilized elsewhere.”