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Warehouses give ‘predictive maintenance’ a new foothold


Warehouses give ‘predictive maintenance’ a new foothold

Published 9 November 2022 in Innovation • 4 min read

PM was one of the most promising applications in the Industry 4.0 revolution, but for years it struggled to find traction. Thanks to unexpected new markets, all that looks about to change. You really don’t want to get locked out of your warehouse…

Predictive maintenance (PM) has long been a prominent capability amongst the suite of technologies ushered in under Industry 4.0. A combination of Internet of things (IoT) and machine learning (ML), predictive maintenance aims to identify potential machine failures before they occur. It does this by collecting key data and finding buried, hard-to-spot patterns that presage a breakdown. The benefits include less downtime, reduced maintenance costs, and smaller spare parts inventory.

PM has seen some success in implementations in energy. These applications are a particularly good example of the “sweet spot”, where PM’s implementation is best suited: the confluence of moderate failure points, data capture capability, and high economic stakes. In some industries, such as aviation, PM is even fostering new business models that offer PM-as-a-Service. This serves both to expand the reach of the PM benefits and the access to the raw data that improves algorithms.

Surprisingly, however, our anecdotal feedback in discussing PM with operations executives is that it is not really gaining traction in manufacturing, despite the fact that for many people Industry 4.0 is inextricably linked with smart factories. The European supply chain director of a major consumer goods manufacturer, one with demonstrated leadership in supply chain digital transformation, told us that “we looked carefully at PM but just didn’t see anything there for us”, as far as their factories were concerned.

A surprising new market

Looking outside factories, Gradesens, a Swiss firm specializing in PM applications, has found an attractive new application for the technology in the world of intralogistics. By applying PM to the automated systems that load and unload very narrow aisle (VNA), warehouses offer all the benefits of PM in terms of minimizing unplanned downtime and lowering maintenance costs, said Yvan Jacquat, the company’s CEO.

The large-scale automated pallet movers in VNA warehouses are hardly new technology, but adopting them has often been met by fears of being locked out if the system goes down. PM can bring significant new value by analyzing key data measurements that are easily captured, and can tell a story of a machine in need of care. Jacquat explains that an imminent machine failure can be predicted by measuring the trajectory smoothness of a fork movement and other mechanical data. Gradesens has completed trials in Switzerland and Spain. The results show that the company’s PM system enables the detection of 80% of the main critical failure modes and leads to significant unplanned downtime improvements. The findings are sufficiently compelling for one large vendor in distribution automation in Europe to proactively encourage clients to implement PM, to improve customer satisfaction and lower maintenance costs due to unforeseen critical failures. The payback time for the system recovering the installation cost is now down to about 18 months and could well decrease further.

Warehouses give ‘predictive maintenance’ a new foothold

Intralogistics is an intriguing market for PM, as new logistics construction continues apace and vacancy rates are at all-time lows. With consumers demanding ever-faster lead times and prominent logistics issues, the overall level of inventory is increasing. The introduction of PM into VNA-equipped sites also offers valuable reassurance to supply chain managers. When the automated material handling fails in VNA, it is always critical: there is no other way to access the inventory in the racks, and the impact on customer service is immediate. Yet, generally speaking, warehouses are not as mature as factories in applying preventive maintenance. The result is either expensive over-maintenance or high-risk under-maintenance.

The next horizon for PM

A recent report projects that the PM market, currently worth $7 billion, will reach $28bn in 2026: a fourfold increase in five years. With markets such as intralogistics coming into play, this may indeed be possible.

Other markets, such as the automotive industry, also offer promise. One industry research group project annual growth in this space of 28% until 2027. Many individuals have already been exposed to PM applications in private vehicles for engine maintenance, and growth into fleet management would seem to be a clear vector. An R&D engineer for a major tire manufacturer told us of PM being explored for tire maintenance and brake components.

Ironically, we may find that in a few years PM fulfills its initial promise just about every where except in manufacturing.

For further reading on the latest industry trends in the global supply chain agenda, please read this article, based on the third edition of the IMD Global Supply Chain Survey.


Ralf Seifert - IMD Professor

Ralf W. Seifert

Professor of Operations Management at IMD

Ralf W Seifert is Professor of Operations Management at IMD and co-author of The Digital Supply Chain Challenge: Breaking Through. He directs IMD’s Leading the Future Supply Chain (LFSC) program, which addresses both traditional supply chain strategy and implementation issues as well as digitalization trends and the impact of new technologies.

Richard Markoff

Richard Markoff

Supply chain researcher, consultant, coach and lecturer

Richard Markoff is a supply chain researcher, consultant, coach, and lecturer. He has worked in supply chain for L’Oréal for 22 years, in Canada, the US and France, spanning the entire value chain from manufacturing to customer collaboration. He is also Co-Founder and Operating Partner of the Venture Capital firm Innovobot.


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