IoT in Supply Chain Management

Article

12th November 2024

The Internet of Things, or IoT, was initially talked about in the 1990s by Kevin Ashton, a British pioneer of technology. (1) He envisioned an environment where the Internet was connected to the physical world by a near-universal network of sensors. IoT sensors would communicate across the network and would create an intelligent environment that would provide real-time visibility to billions of data points.

Supply chain management (SCM) is a holistic process that encompasses the entire cycle and flow of services and goods. It begins with sourcing raw components, moves through manufacturing and then on to warehousing, transport and eventual delivery to end customers. SCM minimises risks, lowers costs, increases revenues, and maximises operational efficiencies. IoT, with its ability to provide unparalleled actionable visibility of real-time data, is transforming Supply Chain Management. Businesses can now track every aspect of raw material sourcing, production and logistics instantly.

Real-Time Visibility in Supply Chains

Traditional systems and monitoring programs typically give companies an after-the-fact analysis of what has transpired within the supply chain. With a network of IoT sensors and devices, it’s possible to gather “live” data on what is going on right now across the entire supply chain. It’s helpful to think of the IoT network as thousands, or even millions, of sets of eyes that are observing and reporting on every aspect of the supply chain. The sensors that are deployed give businesses the ability to track and manage the supply chain “live”.

With this visibility, a business is provided with live insights into everything that is occurring at that moment. IoT provides valuable information about warehouse automation, shipment and cargo movement and can even help identify demand patterns, future trends and possible disruptions in the supply chain.

Other innovative technologies can also be used with IoT to complement or improve real-time visibility. Artificial Intelligence (AI) is an advanced technology that enables machines and computers to simulate human problem-solving skills and intelligence, at vast scale. Within the supply chain, AI can use its inherent intelligence to provide timely predictive analytics that are useful in forecasting demand and potential maintenance issues, and instantly flag supply chain deviations that need human review.

Machine Learning (ML), a branch of AI, focuses on the use of algorithms and data to help AI imitate how humans learn, only on a large scale. Like human learning, Machine Learning is constantly improving its knowledge and accuracy. Within a supply chain, ML models are used to analyse huge data sets and identify hidden patterns from previous supply chain operations. Because of the size and scale of the data sets, it’s likely that human beings would have never spotted these hidden patterns. All of the IoT and advanced data sets can be stored and integrated within sophisticated cloud computing data storage environments that also enable enhanced analytics.

The Impact on Inventory Management

Within an enterprise, there are typically several challenges when it comes to inventory management. These include the lack of true real-time inventory visibility, understocking or overstocking and identifying and tracking products that are obsolete. Further issues such as understanding volatility, forecasting demand and integrating real-time inventory visibility with the sales channel are also critical.

IoT simplifies and greatly enhances inventory management solutions. RFID tags and scanners can provide continuous inventory status and monitoring, with data updates to the cloud. RFID tags are smart barcodes or labels that store information about the item they are attached to. They then use radio frequency technology to transmit data from the tag to a reader and in turn to the RFID computer program.

Predictive analytics can also be applied, allowing accurate supply and demand forecasting. An IoT-enabled system can even optimise stock levels by enacting automated replenishment to order new inventory if a shortage is predicted. For example, in the restaurant industry forecasting systems powered by AI use machine learning and historical data to help predict upcoming demand. The forecast demand is then compared to current inventory levels, and the tools automatically place orders, so stock is maintained at the correct levels. (2)

Predictive Maintenance in Supply Chains

Any disruption in a finely tuned supply chain can cause delays and significant problems throughout the remainder of the chain. To keep things flowing efficiently, regular maintenance must be performed throughout the entire supply chain operation. Breakdowns in production, warehousing and storage or transportation can bring supply chain logistics to a halt.

With sophisticated IoT monitoring, it’s possible to employ predictive maintenance. The host of sensors and other devices collect data about equipment performance and status and alerts when upcoming maintenance will be necessary. This proactive approach dramatically reduces downtime and lowers overall maintenance costs. The pharmaceutical industry is benefiting from predictive maintenance, with sensors monitoring refrigeration that is vital to the production of drugs. (3) Utilities can use the technology to sense power outages, and manufacturers can use infra-red sensors to identify faulty machinery that is beginning to overheat.

Quality Control

The numerous IoT sensors allow for sophisticated monitoring and can be used to detect and prevent defects throughout the manufacturing and supply chain flow. They provide a detailed and complete record of the entire manufacturing process, which improves transparency and traceability. The introduction of IoT has also allowed industries to implement comprehensive IoT-enabled real-time alert systems.

When manufacturers integrate IoT devices and their manufacturing systems, real-time data lets them constantly monitor and instantly identify and correct inefficiencies in production or processing. (4) Instead of waiting for end-of-day production reports, they make changes that improve efficiency immediately.

Similarly, the real-time monitoring and instant analysis of production lets manufacturers spot defects and quality control issues right away. (4) In steel production, for example, sensors can instantly measure the steel sheet thicknesses, and any deviation can trigger immediate alerts. This helps ensure quality and also improves efficiency by reducing product waste. (5)

Leading companies have also tapped into the powerful analytics and data-driven decision making that’s possible with IoT. These technologies offer opportunities for greatly improved operational efficiency and the identification of new business opportunities. Food and beverage manufacturers use IoT to regulate and track temperature, humidity and pH levels within their supply chain. Coca-Cola taps into the power of IoT and the cloud to monitor the performance and quality of its vending machines. (6) Within the automotive sector, Bosch uses sophisticated IoT solutions in their fuel injection systems. (6)

Product Recalls

Product recalls can be tremendously damaging to a company’s reputation and may also come with legal and financial liability. The ability to even execute a product recall is dependent on complete and accurate tracking of the goods throughout the supply chain process.

IoT provides comprehensive and continuous monitoring during every stage, from raw material to production to distribution. Because of IoT’s enhanced visibility, problems can be isolated and identified much more quickly. In addition, IoT enables full traceability, which is critical when a product recall is necessary.

Addressing Supply Chain Bottlenecks

Any congestion point within a supply chain can result in a bottleneck that affects the smooth and efficient flow of the entire chain. Bottlenecks can be caused by a failure to correctly forecast demand, a lack of contingency plans, inventory management problems and miscommunication with vendors and supplies.

IoT helps reduce the bottlenecks by providing unparalleled, real-time visibility throughout the entire supply chain. The real-time monitoring of production lines, product shipments and other supply chain processes give managers instant visibility into what is going on. AI-based alerts can further enhance the ability of company personnel to react to and take corrective action on potential supply chain bottlenecks.

Challenges in Implementing IoT in Supply Chain Management

Numerous challenges exist when it comes to implementing large-scale, sophisticated IoT solutions within supply chain management. The cost of rolling out full IoT technology solutions can be high, so sufficient funding must be allocated by senior management. Unlike traditional IT expenditures that span multi-year life cycles, the rapidly changing world of IoT will likely require frequent expenditures and upgrades.

Disruptions in Internet accessibility are one of the primary threats to IoT in a supply chain management environment. To be successful, the organisation must have selected vendors who can provide stable, high-speed Internet available across multiple geographic locations.

Data integration and interoperability challenges can arise when working with multiple stakeholders that have different technical systems. Choosing a vendor who can provide middleware or data integration services, is a must.

Team members and management must buy in to new ways of doing business. With IoT in SCM, the traditional world of after-the-fact reporting is instantly replaced with real-time, instant visibility. Training must be provided so internal teams can adapt to these changes. They will also need in-depth training to enable them to fully analyse IoT’s vast data sets.

Network security and protection are critical since IoT devices open up numerous new connection points that could be vulnerable. Companies will need to choose network security providers who can provide proven protection against data leaks and network threats.

Future Trends in IoT for Supply Chain Management

The global supply chain IoT market is expected to grow from €17.5 billion in 2022 to €32.2 billion in 2027, an incredible 84% gain over just 5 years. (7) Finance Online estimates that there will be 25 billion plus IoT devices that will be in use over the upcoming seven years. (8)

IoT sensors and devices will continue to proliferate, giving near-universal, instant visibility across the vast and complex supply chain. They will be able to track equipment, inventory and all shipments continuously. AI will then be used to flag anomalies and issues. AI-assisted robots and drones will be in use at touchless warehouses. (9)

IoT data in real-time will also be used to generate digital twins, replicas of physical operations within a supply chain. AI will then be tasked with performing multiple “what-if” simulations on the digital twins. Changes will be tested virtually first, minimising costs and risks before real-life rollout. (9)

Over the next few years, we can also expect to see major advances in IoT due to the integration of AI and machine learning. The vast networks of sensors can be proactively harnessed to provide both predictive data and clear insights into every aspect of the manufacturing and logistic supply chain process. Cloud solutions will further enable full data tracking, visibility and unlimited storage for the vast data sets collected within the IoT technology framework.