What Are the Best Ways to Improve Your Machining Operation?

By
EN
Emily Newton
on October 22, 2021

Machining is never a cheap process — it takes significant amounts of time, money, equipment and expertise to do well.

The owners of most machining operations, as a result, are aware of how even small business decisions and process changes can impact productivity and profitability.

For modern machining operations, a few key factors — like maintenance, cutting conditions and training — are the most important to manage.

1. Optimize for Tool Life — But Know Where to Draw the Line

Maintenance is essential to the function of any machining operation.

Optimizing tool life should be the goal, but maximizing may be impractical. For example, if a tool or component is becoming worn down but may still have a few cycles left before it requires replacing, an early replacement may be a better option than continuing to risk failure.

Attempting to maximize tool life can disrupt workflows and make processes harder to optimize, reducing or cancelling out the cost savings you may have secured. Shop practices that balance tool life optimization against process optimization can help you maximize savings.

Changing all the tools in a turret at the same time, for example, can help minimize downtime and make documenting repairs and maintenance much easier. While you may lose some tool life by replacing certain inserts too early, streamlined maintenance can help make up for those potential losses.

2. Use the Right Maintenance Approach

Most business owners consider preventive maintenance to be the gold standard approach for machine upkeep. This approach — which involves repairing, inspecting and replacing components on a set schedule — is effective and typically lays the foundation for most strategies.

A more advanced approach, enabled by IIoT technology, builds on top of a preventive maintenance approach. Predictive maintenance combines condition monitoring with big data algorithms to predict machine failure.

IoT or “smart” sensors gather information on critical operational parameters — like vibration, pressure, lubrication and timing. This information is sent to the cloud, where it can be analyzed by specialized algorithms trained on machine maintenance data. These algorithms can pick up on patterns in operational data to forecast when a machine will fail or need maintenance.

 

The cost savings of predictive maintenance in combination with preventive care can be significant. Some research shows that owners can save 8%-12% over preventive maintenance alone and up to 30%-40% over reactive maintenance.

Reactive and solely corrective maintenance approaches are typically cheaper in the short run, as you’ll only need to turn off machines and make repairs as problems arise. However, these maintenance strategies are also more likely to reduce the lifespan of equipment and can sometimes lead to unplanned downtime.

3. Apply Optimal Cutting Techniques

Small changes to the cutting process — like the arrangement of cutting lines — can have a significant impact on overall machining time.

When laser cutting, for example, techniques like grouping and nesting can help reduce the distance the laser head will need to travel, thus saving valuable time. They can also help reduce cutting waste, which is good for operators trying to embrace lean manufacturing principles.

High precision CNC laser cutting metal sheet

With grouping, pieces are clustered together to help reduce the number of cuts that need to be made. This helps minimize waste and unusable scrap, as well as laser head travel distance.

Nesting is a more complex process that involves placing pieces so that they share common edges.

Both of these processes can be complex and may require assistance from a business partner with expertise in laser cutting — applying them can, however, help reduce the time needed for laser cutting significantly.

4. Optimize Cutting Conditions

Cutting conditions can have just as big an impact on cutting efficiency as the tools you use and the techniques you apply. One study on machining efficiency found that it was possible to reduce setup and machining time by 35% and 55%, respectively, with the right changes to machining order, cast geometry, cutting method and cutting conditions.

Grouping together similar operations where practical — like face milling, boring and drilling — can help simplify the machining process significantly, reducing both the risk of error and the time it takes to fabricate a part.

Cutting speed, feed rate and depth of cut can all have a major impact on efficiency. Finding the optimal cutting parameters using machining simulators and data from previous jobs will help you get the most out of your tools and accelerate work. Smart sensors or similar data-collection technology can likely help you with data gathering here, as well.

milling process of metal on machine tool

5. Employ Smart Machining Technology

In general, lean manufacturing can benefit significantly from smart technology — networked sensors and devices simplify tracking site processes and improve quality control.

Smart technology is also becoming increasingly useful for manufacturers wanting to extend the lifespan of their machines.

For example, it’s good practice to conduct regular tool life and machinability tests over the course of a tool’s lifespan. These tests, which measure wear against tool speed, velocity and depth of cut, provide business owners with hard data on how machining conditions and tool choice impact tool lifespan.

When making decisions about operational parameters or buying new tools, this data is essential and can help an owner significantly extend the lifespan of new tools.

Machining operations that rely on analog maintenance and testing solutions will need to create a regular testing schedule and documentation processes to ensure that tools are regularly tested and information on wear and use is recorded. Data from these tests will also need to be stored in a way that can later be analyzed or reviewed to make more informed decisions about future jobs or investments.

With IoT devices, it’s possible to automate much of this process. Smart devices can continuously record operational parameters, providing optimal data for owners to calculate remaining tool life and tool lifetime expectancy.

Often, if you employ a predictive maintenance solution, you’re already tracking much of this information and have the necessary sensors in place.

The same information can also help you optimize cutting conditions — comparing conditions against the time a project takes, for example, will help you find the optimal conditions to minimize cutting time.

6. Make Data-Informed Business Decisions

Tool choice, operation order, technique, cutting method — for each job, there are many different variables that you have to consider.

Long-term business decisions, like investing in a new machine or piece of equipment, can become even more difficult for this reason.

The best way to improve your ability to make informed decisions is by collecting the right data. Information about your tools — which materials wear down faster or which cutting methods optimize project speed — will help you optimize processes to maximize tool lifespan or pick tools that last longer under the operating conditions of your site.

7. Digitize Tool Documentation

Regular maintenance and testing work best when you have a good documentation strategy. Traditional documentation methods that rely on pen and paper can be effective but often create more administrative work for you and your team while increasing the risk of error when employees are recording or transcribing data.

Digitizing your documentation is one of the best ways to reduce errors and streamline the documentation process.

Colleagues analyzing the annual business report and taking notes in the process

Shops of all sizes can typically afford one or more workstations that make it easy to digitally enter new data on tool performance and maintenance. IIoT systems can automatically send digital records of performance and operational conditions to the same place that manual records are stored.

A standardized documentation process can also help reduce the loss of institutional knowledge as employees rise in the ranks or leave the business.

8. Make Training a Priority

Effective machining depends on well-trained personnel — especially in shops where the labor of processing engineering falls increasingly on machine operators.

Offering onboarding, in-house training and funds for off-site training will help ensure that operators understand the machines they use and have a good sense of how to operate them safely and efficiently.

CNC operator, mechanical technician worker at metal machining milling center in tool workshop inserting data with keyboard wearing noise cancelling headset

Training will help any shop instill good working practices into daily operations — boosting efficiency, reducing risks and potentially extending the lifespan of tools and equipment.

Optimizing a Machine Shop for Efficiency and Productivity

The right technology and process changes can go a long way in improving a machine shop’s productivity. The right conditions, tools and maintenance plan, for example, will help any shop cut down on unplanned downtime and extend tool lifespan.

Training and effective documentation processes will help reduce knowledge loss and ensure that your shop personnel become even more productive over time.

Emily Newton

Emily Newton is an industrial journalist with over four years of experience. As Editor-in-Chief of Revolutionized, she regularly covers this industry and how technology contributes to its evolution.
Emily Newton, Revolutionized

 

*This article is the work of the guest author shown above. The guest author is solely responsible for the accuracy and the legality of their content. The content of the article and the views expressed therein are solely those of this author and do not reflect the views of Matmatch or of any present or past employers, academic institutions, professional societies, or organizations the author is currently or was previously affiliated with.

Leave a Reply

Your email address will not be published. Required fields are marked *