Businesses today manage ever-complex supply chains, facing new challenges in both the planning and execution phases. Fast-changing markets are resulting in shorter product life cycles and consequently, the need for flexibility; lapses in quality are driving calls for improved transparency and consistency; and quicker, innovative delivery options have become a key competitive differentiator. Article contributed by BOGE Kompressoren Asia Pacific.
Broadening applications of IoT-based devices and sensors continue to offer unprecedented solutions in operations, logistics and end-user experience. Yet, the growing accessibility to data has placed additional burden on traditional systems responsible for forecasting, replenishment and maintenance. More companies are developing and employing Artificial Intelligence (AI) across operations to benefit from greater visibility and acuity in decision-making, leveraging disruptive technologies such as robotics, autonomous vehicles, networked systems and machine learning.
“AI is revolutionising the way we execute day-to-day activities, empowering businesses to focus on more urgent, higher-skilled tasks that call for critical improvements in efficacy and output in the supply chain, from warehouse automation to distribution,” said Nalin Amunugama, GM of BOGE Asia Pacific, a leading specialist in compressed air solutions.
Given AI’s vast potential to deliver business value, investment in related capabilities is only set to increase. According to International Data Corporation, AI and machine learning expenditures will grow to US$57.6 billion in 2021, signifying AI’s maturation from game-changing idea to instrumental business tool.
While there has been much excitement over AI, early adopters have typically been digital leaders who are among the largest firms in their sectors. Most companies utilising AI have yet to adopt the technology at scale or incorporate it into their core functions, with its use confined to a number of applications and trials. Joint partnerships have thus become great platforms for businesses to gain access to the relevant resources and skills, helping them move beyond small-scale AI experiments to wide-reaching automation and operationalisation.
Supply Chains and Logistics Excellence.AI (SCALE.AI) is one such initiative that aims to accelerate the development and integration of next-generation AI-powered supply chains. The Canadian industry-led consortium, designated as a federal government initiative in February 2018, brings together 119 industrial firms, enabling organisations and world-class research institutions to collaborate on large-scale applied innovations that will help enhance the revenue and performance of companies of all sizes. Partners cut across industry segments to include companies such as Air Canada, BlackBerry, Bombardier, Intel and Lallemand.
To date, the consortium has committed US$700 million to support projects that tackle supply chain-related challenges. The deployment of cutting-edge technologies focused on data generation and use, algorithm training, IoT interoperability and robotics in these projects present opportunities for better demand forecasting, inventory optimisation and transparency of material flows. The supercluster is expected to create over 16,000 new jobs across Canada and add more than US$16.5 billion to the country’s economy over the next decade.
Smaller-scale collaborative efforts have similarly borne fruit, such as the joint project developed by BOGE Kompressoren and Aventics, which leverages the intelligent networking of compressed air generators and users. Efficient management of compressed air supply is important, especially as the production of this essential utility can be expensive and energy-intensive. The Smart Pneumatic Grid looks to address this concern by using machine-to-machine communications protocol OPC UA to facilitate monitoring and controlling, and ultimately optimise entire system topologies. Recognised by manufacturers across the board, OPC UA is currently the top standard for horizontal and vertical networking in the automation sector.
By identifying the specific energy requirements of individual consumers, the Grid is able to actualise needs-based control rules for the BOGE compressors. Increases in air consumption caused by leaks are also quickly detected, allowing users to schedule maintenance checks well before a machine standstill occurs. The smart system, highly adaptable to fluctuating conditions, effectively unlocks potential for round-the-clock observation and monitoring of air consumption, allowing operators to correct out-of-tolerance lead times and enhance compressor performance at high levels of accuracy.
“Seamless communication between equipment and systems will take precedence in manufacturing facilities of the future, serving as an enabler and multiplier of productivity. Through real-time insights and predictive maintenance, businesses are able to lower energy consumption and minimise supply chain disruptions,” remarked Mr Amunugama.
AI’s emerging capabilities are also making big strides on the roads – particularly in the form of autonomous vehicles (AVs). With the many tests and prototypes introduced in recent years, wide-scale implementation of driverless technologies seems imminent. In fact, AI-enabled AVs are predicted to hit the roads in 2025 and become an established part of the mobility landscape by 2030. Apart from holding the promise of a smoother and safer driving experience, AVs are expected to strengthen efficiency in terms of better traffic flow and lower fuel consumption.
Closer to home, AVs are opening doors for improved logistics and tackling manpower constraints. Last October, Belgian logistics company, Katoen Natie, piloted Singapore’s first driverless truck at ExxonMobil’s manufacturing hub on Jurong Island. Equipped with in-built speed controls and a safety bumper that triggers an emergency stop when necessary, the truck operates 24 hours a day moving goods between packaging and intermediate storage facilities.
If tests are successful, 11 more trucks will be added to make a fleet of 12 – collectively, the driverless vehicles will be able to transport three million tonnes of cargo annually. Transponders, used in an earlier phase of the project, will also be replaced with a more sophisticated global positioning system technology, with the trucks now navigating by satellite. These AVs will help bring down operating costs, allow more freight movement at night to ease traffic congestion, and mitigate the growing shortage of truck drivers.
Koen Cardon, CEO of Katoen Natie, shared: “Normally you need about four drivers for one truck; they will now be replaced by one supervisor who is working from the remote station, so that is a massive improvement in terms of productivity.”
This trial joins other AV pilot programs in Singapore, such as PSA International’s 30 automated-guided vehicles (electric-powered dollies) that move containers in its terminals, and the truck platooning system developed by PSA Corporation, Scania and Toyota to be used on the city’s public roads in the future.
Swifter, Smarter, Leaner
The rapid rise of AI is poised to transform the face of business and how supply chains are understood and optimised. Real, practical applications are already in place and will continue to help companies become more agile, make informed decisions and detect risks as early as possible so that corrective action can be taken. Smarter predictions of demands and consumer trends will also result in more precise inventories and replenishment plans. By 2020, 50 percent of mature supply chains will use AI and advanced analytics for planning, thus eliminating sole reliance of short-term demand forecasts.
No doubt, dedicated strategies must first exist for AI to be properly integrated into business processes, and for significant gains to be enjoyed. For early adopters, AI-driven supply chains – more responsive, intelligent and streamlined than ever – will be crucial in providing much-needed visibility and efficiency, while delivering a competitive advantage and greater profit margins.