Since the early 1700s, mechanization has played a vital role in manufacturing. The Industrial Revolution started in England in the 18th century and quickly spread to other countries, including France and Germany. By the late 18th century, Industry 1.0 boarded sailing vessels and crossed the seas, landing in the Americas.
Before the rise of machines, manufacturing was a labor-intensive process in which everything was handcrafted meticulously, one item at a time, over time. According to most scholars and historians, the first industry to benefit from mechanization was textile production. From the early cotton gin that separated the seeds from the raw cotton to the power loom that increased worker output by a power of 40, machines changed the way fabric goods were produced.
Supply Chain Management Comes of Age
The first documented factory was likely a silk production facility opened by John Lombe around 1721. The machinery was driven by water power to mass-produce Lombe’s products. At the height of its operation, the silk factory employed around 300 people.
Today, nearly every product imaginable is mass-produced by a vast array of machines. In fact, to see goods still produced one at a time by hand, you almost have to visit a Renaissance fair or artisan community!
We’ve entered the constantly growing and evolving era of Industry 4.0, often called the fourth industrial revolution. Where it may take us is anybody’s guess. Machines and equipment are being invented and developed at a near breakneck pace.
All innovation, whether back in Industry 1.0 of the 1700s or in today’s world-class manufacturing, has been driven and is still driven by two all-encompassing factors: the laws of supply and demand and supply chain management.
Balance: The Supply Chain Management Tightrope
Supply chain management can be like balancing a tightrope walk. One misstep and the entire process could very well tumble to the ground. Both the incoming supply of ingredients (whether perishable for food and beverage manufacturing or nonperishable for hard goods) and the outgoing supply of products to consumers need to be as stable as possible.
Of course, you need some excess inventory—but not a massive amount, particularly in perishable product lines. But keeping your machines running at optimal equipment efficiency (OEE) standards keeps this in check barring any unforeseen incidents.
How efficiently and consistently your machines run affects your outgoing chain of supply to the consumer or end user of your product.
The advancements in machine technology help achieve this. Many manufacturing tasks are handled more efficiently, effectively, and consistently by today’s machines than is possible by human hands. However, there’s one characteristic of machines that is similar to their human counterparts, one that has always been there.
They break.
That’s the main reason that machine maintenance is vital to every manufacturer to keep supply chains rolling. It was true in Industry 1.0 and is just as necessary in Industry 4.0—maybe more so, to be frank.
Let’s look at the main models of machine maintenance. You may be quite familiar with two of them. In some respects, the third is a relatively new one to explore—at least some aspects of it.
Preventive Maintenance Models That Affect Supply Chain Management
As mentioned, keeping your machines running optimally affects both sides of the supply chain (although it’s not the only factor). In Industry 1.0 and much of the following industrial revolutions, machine maintenance followed more of a reactive model.
“Run it until it breaks!” was the battle cry. And when it breaks, try to patch it up until proper repairs can be made. This gave rise to the duct tape and baling wire caricatured persona of the old-time maintenance worker.
But duct tape and baling wire can’t fix everything. As a result, a machine remained idle, often for hours at a time or even days, stopping production and disrupting operations.
Downtime can be expensive. It affects both the incoming and outgoing sides of supply chain management.
Eventually, a more proactive model of machine maintenance was devised.
This more proactive model, given the moniker preventive maintenance, is an attempt to prevent downtime by “fixing” failures before they happen. Parts are changed during planned downtime and not during production.
Preventive maintenance came about, in many instances, by a concerted effort between machine manufacturers and maintenance professionals. Machines were run either in production or in test scenarios, and the wear and tear on components was logged, categorized, and cataloged. Individual component builders, such as bearing or gear manufacturers, also contributed to the process.
Mean time between failures were calculated and procedures to extend these times were developed. Lubrication and adjustments are part of those runtime extensions.
Using the information gleaned from these tests and observations, valuable tools were produced to enhance machine maintenance. For example, along with user manuals and operator instructions, preventive maintenance schedules were provided. These instructions included lubrication schedules and parts replacement schedules for items that would wear out. A list of replacement parts that should be kept in stock was included.
Remember, it’s not just product ingredients that can be affected by supply chain issues. Many parts, especially electrical and electronic components, have been deeply impacted by recent supply chain disruptions. Even new equipment has been put on hold as components such as variable frequency drives, power supplies, and user interfaces are difficult to source at times.
Create an Appropriate Preventative Maintenance Plan
A good preventive maintenance plan, including keeping an adequately stocked parts room, affects how you can manage other supply chain issues.
However, there is one downside to preventive maintenance. Oddly enough, over maintenance can be a challenge. Changing parts before they fail is good. But too much of a good thing can be costly. Changing too many parts too soon will eat into your operating expenses. That can lead to premature budget failure.
While preventive maintenance is definitely a step in the right direction, it’s not infallible. Parts still fail when they shouldn’t. Machines still break down right in the middle of an important production run.
Why? And how can this be alleviated?
Many times, the environment in which the machine operates is the culprit. And part of the solution is a somewhat new model called predictive maintenance. In reality, it has been around for a while. But the arrival of Industry 4.0 and the development of smart sensors with the Industrial Internet of Things (IIoT) has enhanced its potential exponentially.
Let’s take a deeper dive into predictive maintenance.
How Enhanced Predictive Maintenance Works with IIoT
Machines operate differently in different environments. Here are two quick and simple examples using electric motors and bearings as the actors.
Heat is the sworn enemy of electric motors. It could be a failed bearing, it could be loose connections, or it could be the ambient temperature it’s operating in. That last reason is often the perpetrator of failures and wasted maintenance money. A motor operating in a cool or cold environment will run cooler and potentially last longer than the same motor running in extreme heat.
For bearings, corrosive atmospheres and washdown chemicals can and do contribute to an early demise. Sanitation, while necessary, has a negative effect on many machine components unless appropriate measures are utilized.
This helped give life to predictive maintenance testing. Two common examples are thermographic scanning and vibration analysis. In thermography, an infrared camera creates a heat signature image of the component and compares it to the ambient temperature and other similar components in the equipment. A wayward part doomed to failure can be ferreted out.
In vibration analysis, sensors are placed on and around the equipment to detect vibration anomalies. If a bearing is damaged, the vibrations from it are detected and charted. Both types of testing—thermography and vibration analysis—can predict when a component will fail, often within a fairly precise estimated time frame.
However, there is one potential issue: If only conducted annually or semiannually, the timing might be off target. The only real method of accuracy is continuous monitoring and logging.
How the Internet of Things Changed Preventative Maintenance
Enter the installation of monitoring sensors adapted for connection to the Industrial Internet of Things. Real-time monitoring is possible by connecting sensors to analytics software that tracks conditions and creates on-the-spot reports of machine health.
Not every potential issue is observable by humans. Sensors see what the human eye cannot. Vibrations may not be sensible to the human touch. But sensors can detect minute variations.
Add to that the possibility that a machine’s slowdown in throughput productivity might be an early warning signal that failure is imminent. All of these conditions have been detected and situations corrected by properly installed and applied IIoT technologies. Many production facilities have not only reduced downtime but also increased their productivity, quality control, and throughput using IIoT-connected monitoring equipment.
Preventive Maintenance Powerfully Enhances Supply Chain Management
Preventive maintenance not only ensures the proper use of your incoming supply chain but also creates opportunities for your outgoing supply to your customers and end users. Keeping your machines running within OEE specs will have a positive impact on your financial future. It’s an investment that brings with it a definite ROI.
If you’re ready to learn more, call one of our Worximity experts today and schedule a free demo or request more information on our products. An investment in enhanced preventive maintenance is an investment in your company’s future.
