The future of Supply Chain 4.0 & beating unplanned downtime

Unplanned downtime is a major concern in modern manufacturing plants, leading to lost revenue, increased costs and reduced productivity. Lengthy shutdowns can cause delayed deliveries, dissatisfied customers and even a loss of business. Additionally, there are intangible effects, such as halted production lines leaving shop floor staff feeling frustrated and purposeless.

In short, unplanned downtime causes serious problems and should be avoided whenever possible. Manufacturers must look towards the future of Supply Chain 4.0 to minimise downtime and ensure the operational efficiency crucial to their success.

The cost of unplanned downtime

The statistics tell the full extent of the story. Research shows that unplanned downtime costs industrial manufacturers as much as $50 billion annually [1]. Such loss of output costs Fortune Global 500 companies 11% of their yearly turnover – worth a staggering $1.5tn. [2]

The impact of downtime varies significantly between larger and smaller companies. Smaller firms can lose anywhere from $137 to $427 every minute. Meanwhile, larger businesses can be out of pocket by as much as $16,000 per minute ($1 million per hour). [3] But when the relative difference in turnover and profits is considered, the impact can be equally detrimental.

The benefits of predictive maintenance

Addressing this critical issue requires modern solutions. Traditional maintenance methods continue to evolve, mainly through the increasing adoption of IIoT (Industrial Internet of Things). All across the shop floor, manufacturers are installing sensors on their machinery. These sensors can collect data on parameters like temperature, vibration, pressure and fluid levels.

The data can be processed in situ through edge computing. Data can also be sent to a central platform for storage via wireless networks. Analytics can then comb through the information to spot patterns, trends and abnormalities.

This statistical data is invaluable for identifying when machinery is malfunctioning. Engineers will receive alerts when specific outliers are detected, allowing them to address issues before any unplanned downtime occurs.

Predictive maintenance technologies are a powerful new addition to the maintenance toolkit to help address downtime in manufacturing. Predictive analytics and condition monitoring offer real-time insights into equipment health. The need for physical presence and manual information collecting is further reduced by remote monitoring and control technology.

Manufacturers can proactively detect anomalies and potential failures, allowing them to promptly intervene and resolve issues before they become critical. This can be done even if they are not physically present at the site.

The evolution of predictive maintenance

Over time, the practice of predictive maintenance has expanded beyond manufacturing and industrial plants and into other sectors, including water and energy utilities.

McKinsey has observed a major change in predictive maintenance (PdM) strategies in recent years. Some pioneers are now implementing PdM 4.0, which involves using full-asset multisource analytics.

As stated by McKinsey, it is crucial for more companies to adopt PdM4.0. This recommendation is based on the identification of five golden rules that can help companies successfully implement such strategies on a large scale. [4]

The 5 golden rules of implementing PdM strategies to reduce unplanned downtime

1. Be informed about which assets to include
2. Consider the right partners
3. Provide sufficient time to improve models
4. Put people first
5. Build predictive maintenance into the organisation's broader digital ecosystem

Welcome to the future of supply chains: Supply Chain 4.0

Advancements in predictive maintenance are evident, but what are the next steps? How will rapid advances in technologies such as AI help manufacturers reduce downtime and operate smarter supply chains?

What is Supply Chain 4.0?

The answer lies in Supply Chain 4.0, the next evolution in supply chain management. This concept incorporates technologies like AI, IoT, cloud computing, data analytics, robotics, and systems integration. These technologies work together to enhance efficiency throughout the supply chain. [5] Supply Chain 4.0 aims to create intelligent and responsive networks by emphasising real-time data, visibility and connectivity between suppliers, manufacturers, distributors, and customers.

It is recommended by McKinsey that businesses "place sensors in everything, create networks everywhere, automate anything, and analyze everything". This is to fully realise the capabilities of Supply Chain 4.0.

Companies can enhance their performance and customer satisfaction by using real-time data, predictive analytics, simulation tools and advanced robotics. These technologies allow for process optimisation, resulting in increased speed, flexibility, accuracy, and efficiency. Moreover, the implementation of Supply Chain 4.0 can be approached incrementally, allowing for affordability and manageable integration.

How Supply Chain 4.0 can help you beat unplanned downtime?

Supply Chain 4.0 holds significant relevance for addressing unplanned downtime through enhanced automation, transparency, and connectivity across the supply chain. By easing the shift from reactive to predictive maintenance, it gives businesses extra support. By doing so, they can foresee and prepare for possible disruptions and learn how to make their supply chains more resilient in general.

Physical assets such as sensors, smart devices, RFID tags, and connected machinery are pivotal in Supply Chain 4.0, bolstered by supporting digital technologies. Warehouse automation solutions like sorting systems, conveyor systems, ASRS, AGVs, and AMRs play crucial roles in improving inventory visibility. Integrated Warehouse Management Systems (WMS) enable real-time inventory tracking across entire facilities.

For example, in an automotive manufacturing scenario utilising Supply Chain 4.0, sensors on assembly line robots continuously transmit data. Machine learning algorithms analyse this data to predict potential failures in robot arms, automatically triggering repair orders preemptively. Simultaneously, the WMS monitors specific part stocks and initiates replenishment orders when necessary, ensuring uninterrupted production flow and preventing unplanned downtime.

Looking ahead, future advancements in supply chain management could leverage AI for fully autonomous operations, encompassing demand forecasting, procurement, logistics, and warehouse operations. Technologies like self-driving vehicles and delivery drones may optimise delivery routes, while blockchain technology could enhance transparency by providing real-time information on the movement and condition of goods.

While these advancements may seem ambitious, the rapid pace of technological progress suggests that such developments are within reach, promising transformative benefits for supply chain resilience and operational efficiency.

Partnering for more robust supply chains

The transformative influence of smart supply chains will be felt along the value chain. This will prove particularly useful for minimising machine downtime. The rising adoption of predictive analytics, IoT sensors, and interconnected systems provides manufacturers with unprecedented real-time insights into machinery health and performance.

Having foresight enables data-driven decision-making and unlocks proactive maintenance strategies. As a result, costly disruptions and unexpected machine downtime are reduced.

Whatever the future of supply chain 4.0, there is one thing that remains constant. Working together and forming a strategic alliance with parts suppliers is vital for a smooth adoption process.

Where EU Automation can help

Building strong relationships with global companies such as EU Automation, logistics partners, and technology providers has many benefits. It enhances the availability of replacement parts when needed. As well as, paving the way to a networked ecosystem where information flows seamlessly and continuously.

The benefits of such an ecosystem extend beyond managing machine downtime. It provides manufacturers with a strategy to succeed in the face of increased uncertainty and disruptions to their supply chains. Companies can build a resilient operation that is ready to meet the demands of the future. This can be achieved by incorporating advanced technologies, fostering collaboration, and embracing a forward-thinking approach.

Sources:

1. https://www.forbes.com/sites/forbestechcouncil/2022/02/22/unplanned-downtime-costs-more-than-you-think/?sh=331c184036f7
2. https://blog.siemens.com/2023/04/the-true-cost-of-downtime/
3. https://www.pingdom.com/outages/average-cost-of-downtime-per-industry/
4. https://www.mckinsey.com/capabilities/operations/our-insights/prediction-at-scale-how-industry-can-get-more-value-out-of-maintenance
5. https://www.gep.com/blog/technology/the-new-normal-for-supply-chains#:~:text=It%20is%20an%20approach%20that,of%20artificial%20intelligence%20(AI).
6. https://www.linkedin.com/pulse/predictions-2024-how-ai-get-us-closer-completely-supply-soham-chokshi-o6pif/