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Get Ready: Here’s How to Reduce Downtime Waste

Get Ready: Here’s How to Reduce Downtime Waste

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Can you accurately report on machine downtime, and do you know what that wasted downtime costs you?

This post discusses how to use equipment downtime data to your advantage.

Tracking Equipment Downtime in Manufacturing

Downtime can happen for many reasons, including operator error, planned preventive maintenance, shift changeovers, and equipment malfunctions. It’s not difficult to loosely equate an idle or non-functioning machine with lost profits. However, historically, this is a rough estimate at best.

Think about the time before the advent of digitally connected machinery and IoT ecosystems in manufacturing plants. Downtime tracking relied on observant employees reporting downtime events using paper records. This method was time-consuming and a bit too random. Furthermore, it created silos of information and prevented teams from streamlining their work across departments, teams, and production lines.

Needless to say, monitoring equipment in real time was difficult. Nowadays, however, the widespread use of automated machinery allows production managers and maintenance supervisors to collect and analyze real-time data directly from their equipment. Having all this information at your fingertips is excellent. But if you’re not acting on it, you may leave profits on the table.

Collecting data is the first step in reducing downtime waste. Here’s how you can strategically act on it to boost efficiency in your organization.

“Predictive maintenance is a critical use case for companies undergoing smart operations and factory or facility transformations. It involves the capture of real-time and historical machine health data over its life cycle to diagnose specific issues before they cause downtime.”
DeLoitte

What Downtime Data Can Reveal

Being able to track equipment downtime, both planned and unplanned, gives manufacturing professionals clear insight into how much inefficiency is present in their factories.

And once you’re accurately tracking downtime, you can apply root cause analysis techniques to locate issues, address problems, and reduce the amount of downtime waste in your company.

So what insights can you gain from collecting downtime data?

The Correlation between Downtime and OEE

Tracking metrics that indicate the contrast between uptime and downtime is critical in understanding overall equipment effectiveness (OEE). OEE calculates how productive your production processes are using a combination of asset availability, equipment performance, and the quality of the finished product. Without downtime data, it’s complex to calculate OEE because machine availability is only one of the three main factors in OEE.

  • To calculate OEE:OEE = Availability * Performance * Quality, where:
    • Availability = Run Time / Planned Production Time
    • Performance = Planned Production Time – Stop Time
    • Quality = Good Count / Total Count

Organizations looking to achieve world-class OEE ratings should aim for over 90% across these three factors, so you should closely monitor both planned and unplanned downtime.

Real-Time Maintenance Requirements

When you’re closely tracking uptime and downtime, you are better able to respond immediately to unplanned, urgent breakdowns (aka reactive maintenance) and quickly mobilize maintenance personnel.

Onboard machine monitoring systems allow technicians to diagnose and act on faults quickly–sometimes even remotely–to get your equipment back up and running fast.

Equipment failure is never ideal, but company leaders focused on profitability can minimize the damage simply by monitoring their downtime and quickly putting out work orders to rectify the problem.

“The digital age of manufacturing allows a plant to be more efficient, traceable, predictable, and manageable than ever before.”
deloitte

Visibility into Productivity

One of the most beneficial aspects of machine downtime tracking is seeing the hard data on expected and actual productivity.

Furthermore, downtime tracking software provides a 360-degree view of which equipment you are not fully utilizing and why. With this data, you can become more specific with your continuous improvement efforts. Analyzing downtime reasons for each machine and separating planned downtime vs. unplanned events will help your team streamline workflows to reduce downtime levels in the future.

Let’s look at how to dig into the data your downtime tracking systems produced.

Acting on Your Data: Reducing Downtime Waste

The acronym DOWNTIME is a convenient framework for analyzing how and where to improve your processes. This stems from Lean methodology and highlights the eight wastes that can occur in your manufacturing process.

DOWNTIME

  • Defects
  • Overproduction
  • Waiting
  • Not utilizing talent
  • Transportation
  • Inventory excess
  • Motion waste
  • Excess processing

Using this framework as a guideline, you can collect production downtime data, total downtime rates, and shop-floor insights from your team. All this information will help you map out where machine data intersects with opportunities for improvement.

An excellent way to visualize this is by using a Pareto chart, a bar graph that reveals the most pressing issues to be addressed first. In addition, with the chart, you can add your downtime data and assign wasted time or money values to each piece of equipment.

Calculating MTTR and MTBF

For example, an aging machine may frequently return faults, causing production bottlenecks on the plant floor and creating unnecessary downtime. Suppose you’re using a computerized maintenance management system to track metrics like mean time to repair (MTTR) and mean time between failure (MTBF).

  • To calculate MTBF, divide the total uptime of a repairable asset by the number of failures of that asset within a given period to arrive at an hourly measurement.MTBF = Total Uptime of Repairable Asset ÷ Number of Failures of Asset within the given time period.
  • To calculate MTTR, divide the total downtime (the total maintenance time required to get the asset up and running again) by the number of times the asset in question has failed within a given time.MTTR = Total Maintenance TIme ÷ # of Repairs

In that case, you’ll have a stack of data you can pull from to map out how, when, and why this issue is happening, along with how many wasted hours it’s costing you.

In addition, with this information, your team can confidently approach the decision-making processes, generating solid solutions to help boost equipment uptime.

Reduce DOWNTIME with SOPs

Writing standard operating procedures isn’t a one-time thing. Managers need to revisit them consistently as workplaces evolve. SOPs for quality control, regulatory requirements, and health and safety require routine updates to stay relevant.  

We hope you’ll refer to the acronym DOWNTIME when writing your next round of SOPs. Eliminate the eight types of waste in your processes to maximize efficiency, increase productivity, and enhance job satisfaction.

Want to streamline process management even further? MaintainX allows teams to create, fulfill, and monitor digitized SOP checklists from their smartphones in real time. Our Computerized Maintenance Management System (CMMS) also users to:

  • Create reusable SOP templates with hierarchical checklists
  • Create, assign, and track recurring work orders
  • Organize assets, parts, and inventory data
  • Instant message team members

Slash Downtime Costs with MaintainX

We’ve shown how reducing downtime costs (and boosting your bottom line) can come down to having the correct data available.

Integrating machine utilization data and a computerized maintenance management system (CMMS), like MaintainX, with your ERP system gives you a comprehensive, high-level view of where you can tighten up efficiency. This will ultimately help you find and improve machine downtime rates for better profitability and customer satisfaction.

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Caroline Eisner

Caroline Eisner is a writer and editor with experience across the profit and nonprofit sectors, government, education, and financial organizations. She has held leadership positions in K16 institutions and has led large-scale digital projects, interactive websites, and a business writing consultancy.

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