Using Automation to Improve Supply Chains

Using Automation to Improve Supply Chains

The pandemic disrupted and damaged global supply chains to the point that, two and half years in, we’re still experiencing critical shortages. Exacerbated by the massive adoption of e-commerce, the disruptions have put supply chains in the spotlight. And, as with many other aspects of the pandemic, it has also accelerated the adoption of technology solutions to meet the new challenges. Industry 4.0 technologies like IoT, AI, machine learning, 5G and digital twins are now driving automation and robotics across the industry.

Five years ago, DHL did an often-referenced survey in which they found that 80 percent of warehouses were completely unautomated and, of the rest, only five percent, fully automated. Since then, the picture has changed significantly, with automation expected to grow at a CAGR of 13.6 percent between 2021 and 2025, according to a Global Warehouse Automation Market report. In last year’s report from MHI and Deloitte, 49 percent of supply chain leaders had accelerated spending in digital technologies to make their operations more agile and responsive. Cloud computing, robotics, and inventory/network optimisation tools saw the biggest jump in terms of supply chain investment.

Data-driven insights

Whether it’s a manufacturer that relies on a just-in-time inventory systems or a retailer trying to manage a front-end e-commerce site, having data on where goods and materials are in the supply chain is becoming critical. Yet, a common complaint of both B2C and B2B suppliers during the pandemic has been the lack of visibility into where products or materials are hung up and when they can be expected to arrive. This makes production planning very difficult for manufacturers and, for retailers, it’s hard to manage customer expectations.

As goods move through ports to ships, trains and trucks on their way to local warehouses, they pass through multiple grey areas where real-time data on payloads is simply not available, often because they are using paper-based systems. Although usually implemented to help reduce the time required to search for items, digital inventory tracking systems are becoming essential throughout the supply chain to provide transparency to upstream and downstream clients.

Digital data is the lifeblood of most modern logistics systems. The most advanced systems can model the end-to-end process as a digital twin, using AI and machine learning to analyse and predict arrival times, bottlenecks and even predict shortages. The Achilles heel of these systems, however, is not having all the relevant data in real-time. Without end-to-end transparency, planning, pricing and delivery commitments can all be affected, meaning lost business, rising costs and reputational harm.



The drive towards digitalisation is also key to automating the supply chain. There are a variety of automated systems within warehouses such as modular conveyor and overhead systems that help to deliver goods to human and robotic pickers for bag order fulfillment. There are also palletised and non-palletised automated storage and retrieval systems (AS/RS) such as those being pioneered by Ocado and Amazon. All these systems rely on real-time data being collected through RFID and BLE tags, bar codes or using optical character recognition to track objects.

The data collected on handled goods is used by warehouse automation software to optimise warehouse processes and provide visibility of goods across the distribution center, as well as to upstream and downstream partners. There are even optical scanners that use AI and machine learning to not only identify the product, but also, to assess its condition and identify handling process issues.

Purpose-built warehouses using systems such as the grid system developed by Ocada are the exception. Many third-party logistics (3PL) operators deal with small, multiple SKU orders and short delivery times. These operators need more agile, automation systems that can adjust quickly to different kinds of inventory. Rather than fixed material handling/conveying systems, they are turning to autonomous mobile robots (AMRs). Through data exchanges with other AMRs and the central warehouse management Fleet Management software, these robots can dynamically adjust their routes in real-time to avoid other AMRs and, based on predictive analytics, adjust routes in real time to optimise batches and pick paths.

"The events of the last couple of years have shown the urgency with which we need supply chain digitalisation and automation"

Private wireless connectivity           

A keystone technology for automation is industrial-grade wireless connectivity such as LTE/5G, Wi-Fi and low-power sensor networks. For cloud-based warehouse management software systems to be able to analyse and optimise the end-to-end workflows, they need to connect tablets, RFID and BLE readers, robots, and personnel. For 3PL operators, whose configurations often change with supplier contracts, robust wireless coverage gives them the flexibility and agility they need.

Where the use case requires mobility, as with AMRs, cellular communications such as LTE and 5G are essential. Some AMR systems have been implemented on Wi-Fi, but Wi-Fi was not designed to support mobility. Thus, AMRs on Wi-Fi are prone to losing the connection and need a technician to restart them, often several times per day. As well, LTE and 5G provide reliable coverage in high-ceilinged warehouses and outside in the yard. Unlike Wi-Fi, they offer quality of service (QoS), which allows the network to be precisely configured to reliably support the application requirements.

Beyond some of the use cases already discussed, there are also multi-modal tablets and heads-up displays for improving the productivity of warehouse employees, virtual and augment reality training, positioning systems for AMRs and the use of drones and robots for local delivery, all of which require reliable broadband wireless communications to deliver.

As-a-service solutions

The advantages of digitalisation and automation are well understood, but many logistics operators have been reluctant to invest the capital in bespoke automation systems. Early proofs of concept, however, are giving way to more modular, flexible systems. There are also third-party offerings that provide wireless campus support as a service, which allows operators to implement limited applications, scaling up coverage as their automation ambitions grow.

The events of the last couple of years have shown the urgency with which we need supply chain digitalisation and automation. Fortunately, the technologies to make it happen on a large scale are here. From robotics and sensors to machine learning and robust wireless connectivity, the pieces are falling into place so that the industry can start creating the kind of touchless, insight-driven and adaptable supply chains that will bend, not break, in the face of market changes.

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