Machine monitoring in industrial manufacturing

By implementing automated, real-time data collection for key steps in a manufacturing process with the help of machine monitoring, you get an accurate and comprehensive database that can be used to drive improvement at all levels - from the plant operator to the line supervisor to the plant manager.

What is machine monitoring? 

In manufacturing, the supervision of machines or machine monitoring is the method of using sensors to collect data from key pieces of equipment in your manufacturing process. In any process, the most important manufacturing equipment to monitor is the limiter.

The machine monitoring provides real-time visibility into manufacturing operations, visibility that helps drive improvement from the top floor to the shop floor.

The collection of sensor data, combined with machine monitoring software, allows production data to be viewed and analysed, transforming real-time data into historical data and analysis. If done correctly, this provides a wide range of actionable information regarding manufacturing processes, including a full set of OEE and TEEP loss metrics, and insights into where the most important process improvements can be made.

Find out more about how to use TEEP (Total Effective Equipment Effectiveness Performance) to improve plant efficiency.

How does machine monitoring work? 

The ultimate goal of the machine monitoring is to gain an in-depth understanding of all aspects of the manufacturing process, allowing an in-depth view of production data at machine, plant and company level.

With sensors, data for more than 100 actionable and meaningful metrics can be generated and distilled into easily digestible reports and, more importantly, a basis for action. Managers, supervisors and operators have a unique role to play in ensuring that a machine monitoring system is used effectively.

The role of the plant manager in machine monitoring

During planning and preparation, it is recommended that the plant manager reviews the high-level business objectives to determine the manufacturing KPIs to focus on. A good question to ask is which KPIs do we need to improve to achieve the greatest business impact? Know the 25 best examples of industrial manufacturing KPIs for production reporting.

Another key responsibility of the plant manager during planning and preparation is to define the underlying policies and standards associated with the machine monitoring system. For example, standards could include:

• Capture a reason for each downtime event.
• Capture a comment for each event of inactivity longer than 15 minutes.
• Measure the changeover time from the last good part (previous part) to the first good part (next part).

After implementation, the plant manager's role is to monitor high-level KPIs such as OEE and TEEP. It is recommended that plant managers focus less on KPI values and more on KPI trends to gauge the rate of improvement. Plant managers are then in a good position to make adjustments to the strategy if they do not see the desired rate of improvement.

The role of line supervisors in machine monitoring

During planning and preparation, it is recommended that line supervisors determine the best points in the manufacturing process from which to capture automated data. There may also be some data that needs to be captured manually, such as explanatory comments from operators about really unusual circumstances, such as very long stops or changeovers that far exceed the planned time. In these cases, it is recommended that the line supervisor creates standardised work procedures and trains operators in these procedures so that all data are captured consistently.

After implementation, one of the most important roles of line supervisors is to analyse the data collected and make adjustments to tactics to improve specific metrics. It is also recommended that line supervisors pay close attention to the involvement and motivation of plant operators, especially in the context of meeting or exceeding targets.

The role of plant operators in machine monitoring

During planning and preparation, it is recommended that operators receive training on the new processes. Beyond learning the procedures, it is crucial to ensure that operators understand why their work is important in relation to the overall company strategy to gain buy-in and a sense of purpose. It can be difficult to adapt to changes in work procedures, so ensuring that operators understand how and why their contributions are important helps to maintain their commitment and motivation.

After implementation, the role of the plant operators is to use the real-time machine data to make decisions and adjustments during their shift. For best results, it is advisable to hang a dashboard in the plant in view of the operators to display real-time production data and provide operators with a direct visual feedback loop on their actions. After all, real-time machine monitoring is only useful if the data collected is readily available so that action can be taken to make improvements.

Why is machine monitoring so important?

Machine monitoring brings great added value because it moves decisions and actions from being subjective to objective, from being based on assumptions to being data-driven. In other words, the machine monitoring when implemented correctly, results in comprehensive, highly accurate and objective data that can be easily converted into insightful actions. It creates a single source of truth and provides the basis for your manufacturing improvement roadmap.

• Creating a rich database

  The machine monitoring creates a rich and connected database composed of a wide range of metrics. Here are some examples of metrics that can be generated from just two or three sensors.

  Metric category	Representative examples
  Six Big Losses	Loss of Descent, Loss of Cycle, Loss of Start-up Rejection
  Count	Good count, Rejection count, Initial rejections
  Fees	In Rate, Target Rate, Rate Efficiency
  Labour	Labour per good part, labour earned, labour lost
  OEE	Loss of OEE, Loss of Availability, Loss of Performance, Loss of Quality
  Cycles	Execution Cycles, Equipment Cycles, Small Downtime Lost Time
  Production times	Runtime, Downtime, Planned Downtime
  Target	Count, Efficiency, Count Variation
  TEEP	Utilisation, Loss of time, Hidden factory time

  The result of implementing a machine monitoring system is the achievement of a consistent database across all manufacturing equipment from which all employees can draw and make data-driven decisions.

  It is also important to note the difference between data and information. The machine monitoring starts with data collection, but the goal is to turn that data into actionable information.

• Generating accurate and unbiased data in real time

  Another significant benefit provided by the machine monitoring is highly accurate and unbiased data. Because it makes data collection a largely automated process, automated monitoring eliminates elements of human error and unconscious bias. Because the data is delivered in real time, the team can move from being reactive to being proactive. Find out more about these types of maintenance by reading this comparison between proactive maintenance and reactive maintenance.

  Companies usually have a reasonably accurate understanding of quality losses. On the other hand, companies are often surprised when they discover the true extent of downtime and how much manufacturing time is lost due to slow cycle times and minor stoppages. It is therefore necessary to have an accurate understanding of manufacturing production losses in order to deal with them effectively.

• Enables the team to act with confidence

  Once you have a timely and accurate information base, you are well positioned to turn that information into results. The IDA (Information, Decision, Action) framework is strongly recommended as an easy and effective way to transform the information generated by machine monitoring into results that drive the bottom line.

  The machine monitoring provides the team with the ability to look forward instead of backwards at missed opportunities. Monitoring production without taking action brings no benefit to processes or bottom-line profitability. However, taking action is also where many companies fail. It is much easier to systematically collect data than to systematically take action on that data. This is why it is so important to organise data into actionable information. For example, when data is organised into Maximum Losses, it is immediately clear where improvements will have the greatest impact.

  A simple but effective improvement strategy is to select the biggest production loss where the team has ideas about actions it can take, minimal external resources are required and actions can be taken immediately.

• Adding value to integrations

  The systems of machine monitoring add even more value when integrated with an ERP or MES system. There are two key integration points:

  The first integration point is to have the ERP or MES provide key values, such as ideal cycle time or takt time, to the machine monitoring system. The most common cause of inaccurate OEE scores is ideal cycle times that are too high. Machine monitoring software can report this with real-time alerts or through historical analysis by detecting when Run Cycle Times are faster than Ideal Cycle Times or by detecting when OEE Performance is higher than 100%.

  The second point of integration is the transfer of KPIs for completed jobs or part runs to the ERP or MES so that job costing and part numbers are accurate, and so that more precise data is available for scheduling.

  If you are not yet using an MES system, we give you 10 tips before implementing an industrial MES system.

Types of machine monitoring

Monitoring of machines for different manufacturing processes

The machine monitoring is applicable to a wide range of manufacturing processes, especially in discrete manufacturing. For example, stamping, bottling, labelling, packaging, moulding, assembly, forming and printing are all within the scope of machine monitoring.

The particularly interesting aspect of this is that almost any type of discrete manufacturing process can be monitored in a similar way with similar metrics. This makes it easier to analyse and collect data consistently across the entire plant or even across multiple plants.

The goal of all these manufacturing process applications is the same: to track machine data and leverage it to create positive change. The way to do this (by tracking losses using OEE and the big six losses) and the reason for doing it (to eliminate waste in the constraint) remains the same, regardless of the type of process being monitored.

Machine monitoring for the EEO

OEE machine monitoring is truly transformative because it allows you to look at all manufacturing processes from an efficiency point of view. OEE and related metrics, such as the Big Six losses and TEEP, were created to serve as machine monitoring metrics, hence the equipment part of Overall Equipment Effectiveness.

OEE machine monitoring also has a very low barrier to entry. You can start with just two sensors and an ideal cycle time for each part. This allows the OEE software to generate a complete portfolio of OEE metrics, six major losses and TEEP.