Data here, data there, data, data everywhere. Many manufacturing plant managers find themselves overwhelmed by the growing volumes of data that their systems collect. Much of the information is simply noise, metrics illustrating that systems are functioning normally. Amidst the clutter is a significant data point or two, but they are often glossed over. So, what steps can suppliers take to ensure they leverage such information?
Manufacturing plants and supply chains track hundreds, thousands, and millions of items moving literally across the globe. Understanding where they are now and where they will be next is vital to optimizing their manufacturing operations. However, almost all suppliers are just at the starting line in their quest to leverage their data for competitive gain. While the vast majority of manufacturers collect data; few analyze it; fewer use it to identify problems; and only a small fraction of these act upon it. So what opportunities are they missing?
Suppliers are constantly on the lookout for ways to lower expenses. MES data can help by identifying areas where resources are wasted, for example, the production line uses more energy than it needs.
Materials are another area ripe with possible reductions. Material lot tracking data analytics improve asset tracking. They trace lot numbers from ERP (Enterprise Resource Planning) work orders through production and associate materials to lots, jobs, work orders, and finished goods. Managers see how long items sit idle and where bottlenecks have been arising. They then make adjustments to improve their yield.
Material usage reporting generates reports on materials by job, shift, day, or other periods. The data can be exported to ERP applications for further financial forecasting.
Material forecasting anticipates material usage/demand based on scheduled jobs and materials specifications. The more accurate the forecast, the more profitable the company is.
The Internet of Things (IoT) enables manufacturers to outfit their equipment with sensors, small special-purpose microprocessors that collect performance data. Because manufacturing machines operate almost continuously during their scheduled run times, IoT devices now provide insight into how well they are functioning. Machine sensors track variable data, like pressure, temperature, humidity, vibrations, acceleration, and power levels.
MES data helps companies in a few ways, starting with troubleshooting. If a conveyor belt stopped functioning, they can examine the variables and determine which one, let’s say increased pressure, was the reason for the snafu.
Traditionally, suppliers managed from behind. Real-time data is key with predictive analytics. Here, the alert is sent out before the conveyor belt stops rather than after. The company then proactively fixes the problem, so the belt does not go down, saving them significant time and money.
MES data can also be used to improve quality. Syscon’s PlantStar tracks items, like Cycle Time, Shot Size, Injection Pressure, Hold Pressure, Hold Time, Cushion, and Position. Production process data including Machine and Tool Cycles, Good and Bad Part Counts, Up Time and Down Time, and Reject, Assist and Downtime Events.
With that information, supplies catch problems earlier in the manufacturing cycle and improve yields because batches are less likely to be tainted. They are far less likely to face product recalls or risk losing customers by delivering poorly made products. Another benefit is they improve their chances of adding new customers from referrals.
Gain Real-Time Visibility
An MES system collects and assimilates data in real time. When a technician records that a particular task is complete, the inventory level is adjusted instantly. Companies gain insights into two key areas: Production Monitoring and Process Monitoring.
The first, Production Monitoring tracks how quickly parts are produced. Process Monitoring measures different variables, such as temperature, pressure, and hold time, that impact equipment performance.
Data collection is a vital step toward understanding how your facility is functioning. The MES solution then uses artificial intelligence, machine learning, and data analytics to create a better understanding of how materials flow, goods are produced, and shipments progress.
Improve Your Supply Chain and Manufacturing Processes
MES data can be used to streamline your process. For example, you may find that the second shift production line runs less efficiently than the first or that every fifth batch of products has a high number of defects. Then, you dig deeper into the data, pinpoint the variables that illustrate why the anomaly arises, and adjust.
Collecting these items empowers manufacturers to enhance their business. They use the data to fine-tune their operation. Possible improvements include:
- Boost productivity by automating routine tasks
- Reduce defective items
- Lower downtime
- Shorten production run times
- Improve customer satisfaction
- Increase profitability
- Raise Overall Equipment Effectiveness
Companies are awash in data nowadays. However, only a smidgen of them leverages the information as well as they could. MES solutions enable them to gain real-time visibility into their operations, reduce expenses, improve manufacturing production, and ultimately improve the business.