IoT Enhances Predictive Maintenance in Manufacturing Shops

The Internet of Things (IoT) adoption in manufacturing has been increasing, but many facilities remain hesitant to fully embrace it. One of the key barriers is a lack of understanding precisely where and how this technology can drive real value at the company. For many manufacturers, IoT predictive maintenance is the most impactful use case.

While IoT solutions have many applications in this industry, ongoing care and repairs are ripe for disruption. Recognizing this potential is the first step toward reaping the benefits of manufacturing IoT.

The Need for Better Maintenance in Manufacturing

Maintenance is both necessary and costly in the manufacturing sector. It accounts for between 15 and 70 percent of the total costs of goods sold, making it one of the industry’s most significant ongoing expenses. However, it does not have to be as disruptive as it often is.

Many facilities rely on run-to-failure repair strategies, which result in substantial downtime and losses from lost productivity. Others use a schedule-based preventive plan, which is more cost-effective, but still entails a high amount of downtime. Conventional preventive approaches may also miss signs of wear before they lead to larger, more expensive issues.

These concerns will only grow as factories grow increasingly automated. Equipment is becoming more mission-critical amid widespread labor shortages and rising output demands. Consequently, downtime, defects, and other machine-related problems will be even more disruptive in the future than they are today, heightening the need for change.

Advantages of IoT Predictive Maintenance

IoT solutions can help by enabling predictive maintenance in manufacturing. This approach uses IoT devices to monitor real-time equipment data to predict future failures and allow workers to schedule repairs before breakdowns occur. Doing so has several significant implications for manufacturers.

Less Downtime

IoT predictive maintenance’s most immediately evident benefit is its impact on uptime. Predicting issues before they cause larger production problems helps manufacturers prevent breakdowns, but the practice goes even further.

While schedule-based preventive repairs can also stave off breakdowns, they require more inspection-related downtime. Because predictive maintenance uses hard data instead, facilities only take equipment offline when it needs service, resulting in greater uptime than the most proactive of conventional preventive methods. 

Real-world results back up these claims. Facilities using preventive and predictive approaches experience 52.7 percent less unplanned downtime than reactive methods. However, those using predictive maintenance more heavily saw 18.5 percent less downtime than those relying more on preventive repairs, indicating it’s the more impactful solution.

Long-Term Cost Savings

Similarly, while manufacturing IoT investments typically incur higher upfront costs, the long-term economic benefits more than make up for them. Predictive maintenance yields higher savings over time than other care methods.

As costly as breakdowns are, they are not the only instance of unnecessary spending in machine maintenance. Routine repairs often result in overservicing and overspending due to investing in unneeded planned downtime and fixes. IoT-enabled predictive maintenance avoids this waste.

In a predictive approach, manufacturers only schedule repair-related downtime when necessary. Operating based on hard data means all maintenance is condition-based, so any investment in this area drives actual results. Consequently, manufacturers can enjoy increased revenue from higher equipment uptime and greater profit margins from lower maintenance-related spending.

Greater Workforce Productivity

Using the IoT to monitor machinery also means maintenance is a more automated process. As a result, manufacturers can direct their technicians to spend more of their time on other tasks. Freeing employees’ schedules this way has two primary advantages: mitigating labor shortages and enabling higher productivity.

Heavy industrial sectors have struggled to get enough workers to meet demand for years now. IoT solutions could help by leaving less work for employees to do. That way, even though labor shortages persist, they’d be less impactful because the facility could still accomplish more in the same time frame.

Some factories may have sufficient staffing levels. In these cases, predictive maintenance’s efficiency benefits would help employees complete more tasks in less time, leading to higher output without a corresponding bump in hiring or working people too hard.

Potential for Long-Term Optimization

In the big picture, the adoption of predictive maintenance in manufacturing opens the door to ongoing improvements. When facilities monitor equipment with IoT sensors, every error or repair issue generates storable, usable data. Over time, this information could provide insight into broader opportunities to optimize operations.

Repeated instances of similar maintenance requirements suggest a larger underlying problem. IoT data could reveal these trends, showing manufacturers if they need to perform a larger upgrade or repair to prevent similar issues in the future. Doing so would yield substantial long-term savings.

Similarly, analyzing IoT data could help factories determine when it’s time to replace a failing piece of equipment rather than sink more money into maintaining it. More informed purchase decisions lead to greater cost-effectiveness.

Best Practices for Predictive Maintenance in Manufacturing

Manufacturers hoping to take advantage of these benefits should consider a few best practices. As beneficial as IoT predictive maintenance is, it only reaches its full potential when companies implement it properly.

First, businesses must identify which equipment will benefit most from this technology. IoT systems can be expensive, and some predictive maintenance efforts have ultimately increased downtime because of high false positives. Applying it only where it’s most effective — often, machines with predictable wear patterns and mission-critical purposes — will help along both fronts.

Secondly, manufacturers should compare solutions from multiple vendors. The ideal partner will help the facility integrate the sensors and get it started to offload much of the technical requirements. Reliable IoT suppliers also meet high cybersecurity standards and offer multiple options to adapt to end users’ unique needs.

Finally, manufacturing IoT initiatives should follow a gradual, data-driven rollout. The key is to apply this technology to one area first and take notes on its successes and challenges to inform future expansions. Monitoring performance and adapting over time are essential to driving the highest possible return on investment.

Manufacturing IoT Is the Future of Shop Maintenance

Manufacturing shops need reliable repair strategies to save time and money. Today, that means capitalizing on the IoT and predictive maintenance.

Implementing manufacturing IoT solutions can be challenging, but the long-term benefits are worth the upfront cost and disruption. It all starts with learning where this technology can help factories overcome common maintenance issues.