How Predictive Maintenance is Changing Supply Chains

The aid of technology has changed supply chains in countless ways, with one of the most prominent drivers of change in recent years being predictive maintenance.

As supply chains get more complex, they require greater oversight and care. As such, with machines and robots and a variety of complex technology comes numerous benefits yet also potential points of weakness. If any of those key components in a supply chain malfunction or breakdown, they can bring it to a complete halt.

An article from GTI Predictive explains,

The cost of failing to manage supply chain systems effectively can be enormous . . . Taking all possible variables into account is critical to maintain steady prices and stay profitable . . . In 2018, supply chain interruptions occurred at a record rate of nearly 30%, costing billions in delays and wasted product.

This is where predictive maintenance comes in. It makes sure machines and robots in a supply chain are well maintained.

This week’s article by Morai Logistics explains just what predictive maintenance is and how it’s transforming supply chains.

What is Predictive Maintenance?

Achieving predictive maintenance comes by having a mindset and the technology to help fulfill it. That mindset involves emphasis on ensuring that machines and robots in a supply chain are actively maintained. Additionally, on the technological front, this approach is accommodated by IoT devices such as sensors that collect data and monitor conditions.

In turn, machine learning is the final component of predictive maintenance. It allows computers to analyze the data collected and makes predictions based off it. With that in mind, just what are the benefits this brings?

Proactive Supply Chains

Predictive maintenance means a foundational shift to how supply chains operate. They don’t have to be as responsive to what happens to them. Instead, predictive maintenance transforms a supply chain into being proactive. For example, it tracks machine health, resulting in machines that are in better condition. That is to say, a supply chain doesn’t have to wait for something to go wrong with a machine to provide it upkeep. Consequently, supply chains can tackle potential problems before they can even become problems.

More Data

With sensors continually attached to the machinery and robotics in a supply chain, data is regularly being collected. Above all, what this results in is a smarter, more efficient supply chain. In addition, as we’ve mentioned before, machine learning and artificial intelligence more generally does not perform well without a sufficiently large pool of data. By having big data to pull from, computers, via machine learning, can make more precise models and accurate forecasts. Therefore, predictive forecasting doesn’t only ensure better kept machines and robots but more knowledge to work with in general.

Less Disruption

By regularly scheduling maintenance on machines and robots as a result of predictive maintenance, the chances of either of them having issues becomes minimal. This is critical, as it means supply chains have a higher likelihood of running smoothly without disruptions. That in turn means more cost-reduction and improved earnings.

Supply Chain Dive explains this in their article on predictive maintenance,

The most common goal of predictive maintenance is improved uptime, with 51% of respondents in a PwC survey last year saying this was their organization’s reason for adopting the technology.

Supply Chain Management - Globalization

Alongside the many opportunities globalization presents for the supply chain industry are potential pitfalls, as such, preparing for them is crucial to the industry’s health.

Globalization has had many positive effects on supply chains. From greater market growth due to an increase in demand, to greater connectivity due the rise of the internet. With that said, the many positives have come with corresponding risks.

Milosz Majta, outlines this in his Forbes article,

Just as there are benefits and costs of globalization, there are similar pros and cons of a global supply chain. In particular, companies need to manage the related risks.

This means that those managing supply chains need to be able to mitigate for these risks if they want to see the upsides of globalization. After all, globalization is like any other major develop in market demand and pressure, resulting in both opportunities and threats. Crucially, the ability for companies to sufficiently overcome these threats is greater than ever. This in no small part being due to advances in machine learning, artificial intelligence (AI), and automation.

This week’s article by Morai Logistics highlights the obstacles that supply chains face as a consequence of globalization and what they can do to solve them.

Harmful External Factors

When managing a supply chain on a global scale, damaging external factors are more likely to come into play. These factors can look like political instability in countries, natural disasters, wars, etc. Ultimately what any of these factors amount to is a potential breakdown in supply chains. If a country’s government is in turmoil, its ports could be affected. If war breaks out, certain supply chain routes may no longer be safe. The same applies to a dangerous weather event. All these factors become more likely due to the scale and variability globalization brings with it.

This a risk that can’t always be mitigated for by its very nature—it’s external. The best a company can do is to have contingency strategies in place for each potential event. Even then, its strategy will ultimately be reactive. In turn, this threat does present an argument for regionalization. As regionalization reduces the problems of scale and instability.


Market demands and trends become harder to prepare for the more actors that can influence a supply chain that are at play. With globalization comes the largest number of actors possible. In turn comes a staggering influx of data which gets increasingly hard to process, analyze, and make predictions off. Thus, supply chain companies have the potential to be floundering in the dark.

Here is where technological advancements become crucial in combatting globalization threats. By being able to automize data entry and collection, as well as process that data via AIs, this threat is greatly minimized. Once data collection becomes an automated procedure, keeping track of data becomes simple. And, with that data, an AI can make predictions and forecasts that make better sense of the market.


More links in a supply chain mean more points of possible weakness within it. With globalization, supply chains are longer, involve more stops, take more time, and include multiple lines of communication. Consequently, this greater complexity requires greater oversight, as even one weak link can vitiate the whole chain.

This byproduct of globalization can be addressed in large part through the technologies mentioned previously. The increasing complexity in supply chains can be simplified by automating processes along it. Moreover, the reliability of a supply chain can be increased by the forecasting of AIs. Finally, the oversight needed along each link in the chain can be better achieved through blockchain technology.