5 Ways Machine Monitoring Impacts Your Business

 

Smart manufacturing is the practice of enabling equipment to collect, process and exchange information over an internet connection. Many companies across the world are integrating IIoT solutions into their facilities.

 

However, implementing even the simplest form of machinery monitoring is not done overnight. For those still working to sell the rest of their team on the importance of machine monitoring, here are five ways machine monitoring delivers impact for your business.

 

  1. Ensuring Quality Parts

Even the most experienced operator struggles to achieve production targets on a new part or project. When it comes to making important decisions about program speed, operator efficiency or another issue; a gut feeling isn’t good enough. Instead, being able to make production decisions based on facts is essential, especially when it comes to manufacturing quality parts.

 

Implementing machine monitoring services provide accurate, real-time data to make faster and better-informed data-driven choices that improve business productivity. Using an online dashboard connected with machine performance data makes it easy to immediately analyze the situation.

 

For example, a review of machine performance data may reveal that the operator is changing the programmed speed to ensure quality parts. This knowledge allows management to work with the machine programmer and the operator to revise the machine’s program and free the operator up to perform other necessary tasks to achieve targets.

 

  1. Improving Operator Productivity

The ability to adjust production is important for success in today’s manufacturing environment. One way of doing this is through automation. With the IIoT, the concept of gathering, processing and analyzing data from web-connected devices and machines is key to establishing a truly automated factory. Proper implementation of automation technologies can help manufacturers react immediately to shifts in production demands and requirements. This is especially true for improving operator productivity.

 

For example, a job shop can review machine performance data from similar machines to identify if there are any inconsistencies in productivity. Should one be revealed to be significantly less productive than others, through deeper analysis it can identify an operator who needs additional guidance and training to reach the productivity level of his/her more experienced colleagues.

 

  1. Increasing Machine Productivity

Various machines fill manufacturers’ shop floors, but often these machines aren’t designed to communicate pressing issues. Machine monitoring software helps translate complex codes into understandable pieces of information. Connecting machines through a network can help them “talk” so operators can determine whether there is a flaw or inefficiency in a manufacturing process.

 

Shop floor data collections provides information about the performance of machine tools, so staff can respond faster to equipment malfunctions and maintenance issues. Understanding machine tool utilization allows workers to quote jobs more accurately and help to reduce lead time. With improved machine tool data collection, manufacturers can get a more accurate view of their processes making them more competitive and efficient.

 

For example, machine data from two identical machines making the same parts can be collected and analyzed to identify if one is less productive and/or has more failures than the other. Further analysis reveals that the poorly performing machine is actually consuming more power to do its job; indicating a need for a maintenance check. Maintenance finds that binding has resulted from chip build up. This indicates a need for the machine to be cleaned and new procedures to be implemented for the operator to perform required housekeeping.

 

  1. Preventing Scrap Production

One of the biggest challenges machine shop personnel faces is visibility to what is happening on the production floor so that activities can be measured, controlled or improved.

 

Automated monitoring systems have the ability to collect meaningful data that can give operators and engineers real-time information about shop-floor activities. Operators can communicate issues to manufacturing managers so appropriate adjustments can be made. Being armed with accurate, real-time data can help company leadership make well-informed decisions that can lead to improved productivity from 20-60%.

A transmission parts maker may see a recurrent drift in a critical measurement, causing too much scrap to be produced. Collection of real-time machine performance data and analysis reveals that the machine feedback trends exactly like the part dimension. This information indicates a need to engage with the maintenance department who can determine that the drive belt needs tightening and create a periodic preventative check to prevent producing scrap.

 

  1. Reducing Facility Energy Costs

Facility executives and manufacturing managers know that corporate budgets can be tight and one way to save money is by reducing energy costs. However, to do this effectively, the proper management of energy consumption must be put into practice. The best way to do this is through industrial-grade machine monitoring that offers the ability to collect real-time data on system energy consumption. What if you could see exactly how much energy a specific machine used within certain time frames? Acquiring this knowledge lies in conducting virtual audits through the IIoT.

 

Here’s a real-life IIoT manufacturing facility example: A Midwestern manufacturing company installed smart devices throughout its facility and discovered it was wasting 20% of its energy. Instead of walking throughout the factory, process engineers analyzed the equipment data through an online platform and figured out how to eliminate the excess power consumption.

 

Another shop receives plant power consumption data. Analysis of this data provides facilities management a graph of consumption against time which reveals that power surges at a shift start time are causing excessive energy cost. Operations managers can now reduce energy costs by 15% by staggering the start times of its departments.

 

Priorities on connectivity cause IIoT solutions like machine monitoring and data acquisition software to dominate many conversations about data in manufacturing. Smart manufacturing promises many benefits, ranging from reduced costs to increased production efficiency. Product defects, unexpected equipment failures, workplace accidents and other preventable issues all cut into profits. Digitalized manufacturers produce a greater number of goods with fewer resources, thereby lowering the cost per unit and increasing their competitive edge. Monitoring your machines today can have great benefits for tomorrow.