How to reduce machine and equipment downtime

Practical steps to minimize downtime involve calibrated maintenance strategies, advanced equipment monitoring and an understanding that downtime events are not just inconvenient bottlenecks but valuable sources of information. 

While the obvious goal of reducing machine and equipment downtime is to maximize machine uptime, downtime events can also be important learning opportunities for maintenance teams. They can identify patterns related to equipment failure and adjust future maintenance plans to avoid future disruptions.

Specific maintenance requirements are often highly dependent on the particular needs and activities of a specific operation. Furthermore, individual maintenance programs rely heavily on the data collected during both scheduled and unscheduled downtime. 

Downtime, whether planned or unplanned, is directly tied to reduced profits. Businesses engaged in manufacturing rely directly on machine uptime and output to create merchandise.

When the equipment these businesses rely on are not producing, inventory stagnates. When a manufacturing business cannot produce the necessary revenue to meet demand, they lose out on those sales and can also lose valuable contracts and sales agreements. They could even face penalties for not fulfilling orders by contractually agreed-upon delivery dates. 

Adding to losses from inventory, production lines that experience a disruption from machine downtime early in the manufacturing process can have exponential downstream effects, leaving on-the-clock workers incapable of proceeding. 

No machine or piece of equipment runs 24 hours a day, 7 days a week, and each experiences both planned downtime and unplanned downtime.

During planned downtime, a business stops machines intentionally according to a predetermined schedule. This process includes scheduled maintenance, changeovers and regular inspections that are built into production schedules.

While machines cannot produce or function during planned downtime, it does offer several important benefits to the overall longevity, capacity and performance of sensitive machinery. Because planned downtime is predictable, this type of downtime can be incorporated into planned maintenance schedules, production timelines, work orders and staffing plans.

Unplanned downtime refers to any unscheduled downtime resulting from sudden breakdowns, human error or maintenance delays (such as delays in acquiring necessary replacement spare parts). Unplanned downtime can often be more damaging for business operations because it interrupts workflows and can lead to cascading effects.  

Here are the top two causes of unplanned downtime: 

• Operator error: Operator error is mistakes made by human workers during the operation, handling or maintenance of machinery. It’s actions or omissions that deviate from correct procedure and result in equipment damage, malfunction or unplanned stoppage. One of the chief catalysts for operator error is inadequate operator training. Complicated machinery requires experienced technicians to properly set up and calibrate. On startup, it’s critical that all run parameters, settings and alignments are in place for a smooth production and operation.   
• Machinery failure: Colloquially referred to as “wear and tear,” machines sometimes break down from excessive use. Although faulty parts or inadequate engineering can cause machine breakdowns, it is usually the overdue maintenance that causes this type of downtime. In practice, a well-constructed maintenance program should prevent this type of breakdown. 

While effective maintenance management can decrease instances of equipment failure and unplanned downtime from breakdowns, some amount of planned downtime is typically unavoidable.

Planned downtime is an important component of maintenance management, providing the opportunity for scheduled maintenance, changeovers and regular inspections. While impossible to completely eliminate downtime, downtime reduction efforts should address both planned and unplanned downtime.

When attempting to reduce equipment downtime, it is important to recognize downtime events as opportunities to capture valuable data.

Through root cause analysis (RCA), maintenance teams gain a better understanding of why downtime happens and develop maintenance strategies to minimize it. With the goal of continuous improvement, these teams gather a range of key performance indicators (KPIs) to develop a robust maintenance program.

The following are some of the most important downtime reduction metrics:

• Mean time to repair: The average time it takes for a machine to get back up and running after breaking down. Mean time to repair (MTTR) includes the time it takes to diagnose, fix and return equipment to normal operation. A shorter MTTR means faster recovery after failure and less downtime. MTTR is a key indicator of equipment reliability. 

• Mean time between failures: The average time equipment operates between unplanned downtime events. Another reliability indicator, a higher mean time between failures (MTBF) means more consistent performance with fewer breakdowns.

• Total effective equipment performance: The overall performance and efficiency of equipment or a production line. Total effective equipment performance (TEEP) is a summation of all the potential operating time, taking into account planned and unplanned downtime, providing an assessment of the equipment’s maximum potential performance.  

• Availability: The total uptime of a machine as measured as the actual runtime divided by scheduled production hours. 

• Performance: The speed of a machine’s output against benchmarks. Performance is calculated as the speed at which it completes its operations against an ideal rate. For example, if a machine produces 700 units in an hour, but has a max capacity of 1000, the performance metric is 70%. 

• Quality: The number of defect-free units produced or error-free operations completed in a single production cycle. Quality is calculated by dividing the number of acceptable process completions divided by the total number of completions. A perfect score of 100% would indicate that every cycle of a specific piece of equipment resulted in acceptable output.

• Overall equipment effectiveness: A valuable metric that combines multiple metrics into a single score for an overall view of a piece of equipment’s general ability. Overall equipment effectiveness (OEE) is calculated by multiplying availability, performance and quality into a single score. 

Whether mitigating unplanned downtime or reducing the necessity for planned downtime, strategies for reducing downtime all share a common goal: more uptime.

Effective methods for reducing machine downtime will vary depending on the specific equipment and conditions in question. Generally, reducing downtime requires robust data collection for a better picture of the equipment’s performance and automated tools for streamlined monitoring and improved maintenance.

Capturing, collecting and tracking reliable, real-time runtime equipment data is essential for effective downtime reduction. All uptime, downtime and runtime can provide useful insight that can be used to inform maintenance programs.

The faster teams collect data, the faster they can spot issues and prevent or recover from unscheduled breakdowns. Without detailed data collection, equipment operators or managers lack the necessary visibility to prevent downtime or respond quickly to potential machine failures.   

Tracking KPIs can help reduce guesswork in reducing machine downtime, but it can also burden maintenance teams. Automated OEE tools can help lessen this burden. These tools eliminate the need for manual data entry and streamline the production monitoring process. 

OEE monitoring software connects to machine sensors to automatically track downtime events, such as short stops, setup changes and failures, with accurate start and stop times. This data is then arranged into organized dashboards and visualizations, revealing trends and providing insight into root causes.

OEE software provides management and maintenance teams with real-time feedback through quickly accessible and readable interfaces. 

Ironically, one of the best ways to reduce machine downtime is to initiate more planned downtime. Because unplanned downtime often comes as a surprise and leads to costly bottlenecks, higher repair costs and wasted employee time, planned downtime for preventive maintenance is a far superior approach.

While running equipment until it requires repair might seem efficient in the short term, proactive maintenance is a far more efficient approach. Reactive maintenance strategies, which wait for machine breakdown before performing maintenance tasks, typically result in more expensive repairs and longer or more inconvenient downtimes. 

Corrective maintenance is reactive by nature—performed only after equipment fails—but that doesn’t make it the wrong choice. For non-critical, low-cost or redundant assets, letting equipment run to failure is often the most practical and cost-effective approach.

Selecting the right maintenance strategy can improve OEE and production output. Some valuable strategies for improving maintenance include:

• Switch from reactive to proactive maintenance: As discussed, preventing unplanned stoppages is typically easier and more cost-effective than waiting for a problem to arise before addressing it. Reactive maintenance, also known as breakdown maintenance, might pay off in the short term, but can lead to worse outages in the future. Typically, many machines will experience planned downtime regardless of maintenance requirements (for example, when machines power down after hours or on weekends). Proactive maintenance can use these planned downtimes for performing any necessary preventive maintenance tasks or deeper inspections. This approach results in less unplanned downtime without even adding any additional planned downtime.  
• Condition-based maintenance for targeted repairs: Instead of relying on a traditional preventive maintenance schedule, condition-based maintenance (CbM) responds to real-time signals and the current condition of your equipment. OEE software can help maintenance teams identify whether and when a machine might fail before it happens. When a machine shows signs of stress, the system can trigger an alert informing operators that maintenance is required. CbM helps maintenance teams address urgent issues right away or better plan when to perform recommended (but not immediately required) maintenance. However, when scheduling non-urgent repairs, it’s important to consider that deferred maintenance—maintenance that should be performed but is not prioritized—can also lead to unplanned downtime. In general, deferred maintenance is only recommended when resources demand addressing urgent repairs first.   
• Predictive and prescriptive maintenance: Predictive maintenance and prescriptive maintenance seek to maximize data and analytics with computerized maintenance management systems (CMMS) to create predictive forecast models for when machinery might fail. They then use prescriptive tools to recommend specific actions to prevent failure and downtime. Combining predictive maintenance and prescriptive tools help avoid unplanned outages, extend the lifespan of equipment and optimize overall resources.