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An ERP system must be fed with insights from several data sources or software systems, and that data must be accurate. Plant performance suffers if the data tracking and analysis are manual or the software is inaccurate. Even if companies use software, it’s critical to use the right combination of software to improve performance.
To address the challenges facing their operations in a hyper-competitive world, manufacturers are increasing performance by targeting three critical areas. Using advanced software to solve the problems in these areas will provide a path to significant improvements.
With up to 22% of the manufacturing workforce expected to retire by 2025, the current skills shortage will only worsen. As many as 2.5 to 3 million manufacturing jobs may need to be filled by then. While training and recruitment efforts will be part of the solution, they aren’t the most significant. More than anything, manufacturers will need to do more with less and at a higher quality.
The solution to the worker shortage will come in software and other technological forces. A Manufacturing Execution System (MES) can automate manufacturing processes and use real-time data and analytics for production activities, improving quality control and increasing performance.
This software increases efficiency and equipment utilization, and operators can run more machines with higher output for each. At the same time, managers, technicians, maintenance, and executives have access to what is happening now and can redirect resources more effectively.
The lack of real-time visualization in manufacturing processes creates uncertainty and leads to guesswork. Operators and managers cannot identify key production issues without clear visibility. This shortcoming makes informed decision-making more difficult for managers and can lead to delays, errors, and wasted resources.
Manual data tracking and analysis are still used in many manufacturing processes, but these methods are time-consuming and error-prone. With so much data missing or incorrect, it’s difficult to identify problems early or make informed decisions on what action is needed.
The solution is clear visualization across the production floor using production monitoring software. A robust production monitoring solution will have advanced dashboards and score boarding. Users can customize their dashboard view of the same KPIs to make decisions relevant to their job. This feature makes it easier to identify issues as they arise and intervene as needed. With software, users see real-time data and metrics, track production progress, and gain insights into the factors affecting productivity.
Manufacturing asset performance is critical for maintaining production efficiency and maximizing output. However, a lack of data on machine conditions and performance can affect machine health, increase unplanned downtime, decrease production efficiency, and put unnecessary pressure on maintenance teams.
Most companies still rely on preventive maintenance. But with real-time data and analytics, they can shift their maintenance strategy from preventive to condition-based, saving the cost of spare parts, reducing downtime, and extending the life of equipment. Access to real-time machine data is necessary to identify performance issues and predict when maintenance is needed. In the same way that a lack of visibility reduces operator performance and increases resources, it degrades equipment health over time.
Asset Performance Management (APM) software allows manufacturers to capture, monitor and analyze critical data streams from machines. This data includes operating temperatures, vibration, power consumption, and other critical performance metrics that help identify trends in machine performance and predict when maintenance is required.
With asset management software, manufacturers can schedule maintenance more effectively. Most OEM equipment companies provide broad guidelines and templates for preventive maintenance, but companies utilize their equipment under a variety of conditions. For example, they may utilize one piece of equipment to produce light-duty products and another to produce heavy-duty products that wear machine components more quickly.
With real-time machine data, maintenance teams can service equipment based on their actual wear and tear, performing some tasks earlier than the OEM guide and others later according to need. This strategy reduces unplanned downtime and increases machine uptime while lowering costs. As machine health improves, so does productivity.
Companies can further optimize their machine health using the software and its insights to develop and deploy condition-based maintenance strategies across all machine assets.
You need a strong digital foundation across your entire operational supply chain to face these challenges. Using a combination of software specifically designed to address these problems will provide complete visibility into your processes so you can automate, optimize, and improve each area.