Maintaining the integrity of warehouse operations is paramount for any manufacturer. You rely on a complex array of machines that play different parts in your processes. Keeping track of your machinery is a full-time job itself, so to expedite the process and ensure continued, ongoing success, you decide to employ a machine monitoring system with your JD Edwards ERP. You know that integrating said machine monitoring system can help prevent breakdowns and harness data for driving better business decisions. But how?
In this overview, you’ll get the inside scoop on three key ways machine monitoring can improve your business processes.
Choosing the Right Machine Monitoring System
Before you get started, it’s important you select the appropriate machine monitoring system for your workplace. It should be compatible with JD Edwards, as well as scalable, user-friendly, and backed by robust customer support. Consider a system that offers customizable dashboards and analytics tailored to your specific manufacturing processes. This feature allows tech teams and floor managers to access real-time data relevant to their needs without sifting through irrelevant information.
When evaluating potential systems, look beyond the sticker price. Consider the total cost of ownership, including installation, training, and maintenance. This includes both the software components as well as any hardware necessary to engage the machine monitoring system, such as sensors that measure temperature or weight. Engage with vendors and request demos to see how their systems integrate with JD Edwards Orchestrator – the conductor that makes effective machine monitoring possible. Ask for references or case studies, particularly from businesses similar to yours. This step ensures you understand how the system performs in real-world scenarios like your own operational environment.
Proactive and Predictive Monitoring
Like the old adage says, it’s better to be proactive and prevent a problem from happening than to deal with the damaging aftermath once it has occurred. With machine monitoring, you can take this one step further with predictive capabilities, too, foreseeing potential problems you might not have even considered.
It starts with data. To act in advance, you need reliable data that paints a picture of your typical warehouse operations. This data can be fed into your machine learning (ML) algorithm of choice, setting the standards for how your machinery should operate. Data will then be collected continuously through the sensors used for machine monitoring. This real-time data can then be used to predict machine failures before they occur, allowing for preemptive maintenance. This proactive approach minimizes downtime and extends the life of your equipment. Amazon, for example, utilizes their own, end-to-end machine monitoring system called Monitron to track the performance of their warehouse equipment. With tools like Monitron, thresholds are set so your team is notified when machines fall out of normal measures; machine learning continuously improves this alert.
With advancements in AI and machine learning, predictive analytics has become a key component of modern machine monitoring systems. The predictive analytics in these monitors alert users to fix issues before they become critical. JDE comes in when automating the work orders to be sure the right department is notified and has a work order to check out the right piece of equipment. This can also be achieved without a JDE integration, but, if you use Capital Asset Management (CAM), the integration eliminates the need for a manual work order entry. This proactive approach not only saves on maintenance costs but also improves machine lifespan and operational uptime. Implementing predictive models to analyze historical and real-time data allows you to foresee and mitigate potential failures, ensuring continuous production flow.
Preventative Maintenance
Regular maintenance is key to the reliability and accuracy of any machine monitoring system. The system’s sensors can monitor product quality in real-time, detecting deviations from specifications early on. This allows for immediate corrective action, minimizing the production of faulty products and ensuring consistent quality throughout the manufacturing process.
In the manufacturing context, there are three types of maintenance: predictive, preventative, and reactive.
Reactive
As the name implies, this type of maintenance takes place after something has failed. While this requires minimal planning, companies that don’t have a machine monitoring system in place to alert them of failures are left playing catch up with fixing warehouse problems. This type of maintenance can be the costliest in the end, with lost time and revenue as a potential consequence of downed machinery. Additionally, further degradation of the machinery may also occur if a problem is not caught early enough.
Preventative
A more proactive approach for a more reliable maintenance strategy is creating a preventative maintenance schedule. Your team can develop an established schedule based on your historical performance data, with regular inspection and equipment servicing. Some machines may need to be maintained on their own regular cadence, too. This maintenance routine catches minor issues before they can snowball into larger problems, leading to reduced downtime and repair costs.
Preventative maintenance can however require significant technician time and resources, and some machinery parts may be replaced unnecessarily.
Predictive
The most advanced strategy is predictive. Instead of waiting for something to break, predictive maintenance helps inform you in advance if a part is on the way out. A machine learning algorithm works with machine monitoring tools, like AWS Monitron to continuously monitor equipment health. Sensors track things like temperature and vibration, sending real-time alerts for any anomalies to make predictions about equipment health and possible maintenance. This allows technicians to address potential problems before they cause complete breakdowns. Predictive maintenance offers the most efficient use of resources, minimizes downtime, and drastically reduces repair costs.
Predictive maintenance not only saves time and money on the part that is being repaired or replaced, but it can also have longer-term supply chain ramifications. If a machine integral to your process goes down, unannounced, at the worst possible time, you could be looking at costly delays – from the machine’s repair to bumping production to another machine to the delay in getting supply off the shelves and into trucks to the delay getting from the manufacturer to the customer. This kind of worst-case scenario domino effect can be avoided, if you’re prepared.
Machine Monitoring Best Practices
Establish a routine maintenance schedule that includes regular checks and updates to both the hardware and software components of the monitoring system. Ensure that your team is trained in basic troubleshooting procedures to quickly resolve common issues without waiting for vendor support. Consider developing a comprehensive maintenance log that tracks all performed maintenance along with any system issues and their resolutions. This historical data can be invaluable for diagnosing recurring problems and planning future upgrades or replacements.
Provide Operations Visibility
Setting up your machine monitoring system is an involved process that requires a lot of planning, foresight, and expertise. That’s why you partner with organizations who can provide a deep level of knowledge and industry trend forecasting to get the most out of your investment. But for day-to-day operations, having on-site personnel who know what they’re looking at is imperative.
Sensors can track various aspects of a production process, like temperature, pressure, or flow rates. By analyzing this data, businesses can identify bottlenecks, inefficiencies, and areas for improvement. This can lead to smoother operations, increased production output, and reduced waste. Your team can access sensor data remotely, allowing businesses to monitor equipment performance and production processes from anywhere. This is particularly beneficial for geographically dispersed operations or for monitoring critical assets in remote locations.
Selecting a machine monitoring system that provides visibility for managers and technicians who are on the floor, dealing with your product firsthand, is a huge benefit to the daily process of your company. You can let your subject matter experts configure and maintain your machine monitoring systems as necessary, and your team is able to oversee seamless operations without needing full administrator access. This is also a safety and security check, alleviating your team from any worries of making a mistake on the backend.
Picking Your Machine Monitoring System
Machine monitoring possibilities are abundant and only continuing to grow in shape, size and sector. Further conversations about the potential solutions these systems can provide, and best practices for different industries, are the next step to improving your business processes.
That’s where we come in. Send us an email and we will get back to you ASAP to help you start your machine monitoring journey.
