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Reducing Waste in Manufacturing with Predictive Maintenance

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Customers don’t pay for waste. They pay only for the materials and processing that add the value they need. Businesses that reduce waste in manufacturing increase their margins and shrink their environmental impact. Along the way, they often find they’re utilizing production assets more effectively and have become more agile.

An important strategy for reducing waste is to implement predictive maintenance. This uses machine health monitoring techniques to prevent equipment failures by optimizing delivery of maintenance services. It raises equipment availability, which increases capacity while improving safety and quality.

What is predictive maintenance, and how does it help with reducing waste in manufacturing? Continue reading to learn more.

Types of waste in industrial settings

Waste takes many forms. While the most obvious are those resulting in material that can’t be sold, waste can come from operational problems, failings and environmental impacts of inefficient manufacturing.

Operational waste

Any time machines aren’t running at full speed to produce what customers want, there is operational waste. The main culprits are inefficient processes and machine downtime.

Inefficient processes are those running too slowly or using excessive resources: energy, materials, lubricants and labor. Machine downtime, especially if unplanned, often leads to workers being underutilized while energy is consumed at the same rate as if the equipment was running.

Material waste

Scrap, rework and overproduction are all forms of material waste. Scrap arises from:

  • Defective or nonconforming product
  • Material used for setup
  • Material consumed in machine troubleshooting
  • Offcuts and remainders of material used in manufacturing

Rework is a material waste because additional material is almost always needed to bring the defective product to a saleable state. Overproduction results in waste because the product might be sold at a discount, or it could sit in a warehouse until it deteriorates to a point where it must be scrapped.

Environmental waste

Any unnecessary resource consumption is wasteful, but additional impacts include greenhouse gas emissions, resources needed for waste treatment, haulage, processing and disposal and the risk of air, ground or water pollution. There’s also the work involved in managing environmental impacts, treatment and disposal.

How predictive maintenance reduces operational waste

By outfitting equipment with predictive maintenance sensors that monitor machine health, it’s possible to anticipate failures and schedule work just before this happens. This reduces operational waste by:

Enhancing equipment efficiency: Failures are usually preceded by indicators such as increasing noise and friction. Predictive maintenance identifies these problems so they can be addressed promptly, which helps machines run more efficiently and without being slowed down.

Minimizing downtime: Predictive maintenance identifies the need for repairs in time for work to be scheduled and carried out before failure.

Optimizing maintenance schedules: Planned maintenance work is scaled back, meaning less planned downtime, fewer maintenance technician hours (so they can be diverted to other PM tasks) and lower consumption of consumables like lubricants, filters and cleaners.

Reducing material waste with predictive maintenance

Predictive maintenance helps reduce material waste in manufacturing. It acts by:

  • Preventing defects and rework: Defects often arise because of changes, particularly deterioration, in machine condition. For example:
    • Bearing wear can lead to variation in rolled material thickness
    • Thermal insulation breakdown can change curing behavior
    • A blocked filter can reduce the effectiveness of a cleaning process

Predictive maintenance helps in identifying such issues, so reducing scrap, rework and material waste.

  • Extending equipment lifespan: Optimizing maintenance intervals can extend equipment life, reducing replacement frequency and the associated waste.
  • Enabling production process optimization: Real-time data on production processes supports optimization. For example, drying times can be adjusted to compensate for moisture content. This helps ensure resources are used efficiently and waste is minimized.

Environmental benefits of predictive maintenance

Predictive maintenance is a key element in moving toward “green manufacturing”. This is where sustainable processes help minimize environmental impact. Predictive maintenance helps reduce emissions and energy consumption while supporting sustainability goals.

In terms of emissions and energy, predictive maintenance ensures equipment is operating at peak efficiency with the lowest possible levels of material and operational waste. It also reduces consumption of consumables, including those with disposal challenges such as lubricants and coolants.

Effective resource utilization, which predictive maintenance helps achieve, is also an effective way of shrinking your carbon footprint. This in turn simplifies compliance with environmental regulations.

Implementing predictive maintenance to reduce waste

Given the benefits of reducing waste in manufacturing, how does a business implement predictive maintenance?

Start by determining what machine health data is already available and how it is or could be used. (Newer machines often come with a host of sensors for parameters like oil condition, flow rate, temperature and pressure.) Then review maintenance records and determine what else would be useful for monitoring machine health.

Many manufacturers find it useful to select a pilot area, such as one where waste levels are particularly high.

Next, explore technology options for filling the gaps identified. IoT sensors, such as those for vibration monitoring, can be especially useful because signal filtering, data transmission and even some analysis capabilities are already incorporated.

Consider too how machine data will be analyzed, stored and used. With the volume of data that can be produced, some manufacturers are deciding that AI-based analytics are essential for gleaning meaningful insights into machine condition.

Having turned data into insights, the final step is to integrate predictive maintenance with the existing maintenance management systems. Predictive maintenance may have limited impact in some non-critical areas, and for those, existing preventive maintenance routines may be sufficient. Remember, the goal is to maximize availability and maintenance efficiency while reducing waste as far as possible, all in pursuit of business goals.

ATS helps manufacturers implement predictive maintenance

This blog has addressed how to reduce waste with predictive maintenance. It has defined the types of waste and, for each one, shown how predictive maintenance solutions can make a direct impact. Perhaps it’s time to consider implementing predictive maintenance in your own operations to reduce waste and enhance efficiency. Contact us to learn how we can help.

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