Artificial Intelligence: The Next Big Thing in Supply Chain Management

Mr Anuj Kapuria
Founder & CEO
Hi-Tech Robotic Systemz Ltd
Co-chair: Robotics Society of India
AI is transforming the dynamics of SCM by deploying smart devices and processes that crunch big data speedily, inferring the right and relevant conclusions faster than human minds. In end-to-end logistics too, the benefits are immense. From mobile robots and self-driving forklifts to other autonomous vehicles, the big benefits of AI are ensuring greater efficiency, cost and time savings, minimal accidents and faster deliveries, among others.

In recent years, drones have attracted public attention due to their impact on supply chains. More than drones, however, another digital age innovation is making a dramatic impact on SCM - Artificial Intelligence (AI).

In understanding its impact, one needs to first understand what AI denotes. Also termed 'machine learning', AI relates to the use of computers in imitating human intelligence. This includes acquiring information, decoding data, classifying the same and then reasoning or deducing insights from the data. Unlike human minds, AI packs the ability to speedily distinguish the 3V patterns - volume, velocity and variety - embedded in big data and discover relevant connections even in varied data.

Increasing Benefits

AI is now present in chatbots, robots, speech recognition software, drones, machines and other devices that use some form of reasoning. Besides accuracy in operations and speed in decision-making, AI has other capabilities that humans cannot even contemplate. Naturally, AI has triggered global concerns and debates about its implications on employment opportunities and the very existence of the human race. While the latter concerns may be premature and misplaced, those on employment opportunities seem more relevant, though these too may be overstated.

Any activity or function that needs to collate and comprehend data of all kinds could gain by using AI in driving swift, smart decisions. Supply chains typically fall into this category and could, therefore, benefit greatly from AI. Deciding inventory levels, network designs for transportation, purchase and supply management, forecasting and demand planning, etc. can all garner productive gains from AI. For example, AI's cognitive tools can track and predict disruptions in supply chains by gathering and analysing external data available from social media, news reports, weather forecasts and even historical information.

Globally, although most supply chains are automated to some extent, numerous mandatory manual chores continue to slow operations. If humans could overcome their reservations about job losses and delegate these tasks to AI, there would be tremendous time and cost advantages. After all, robots don't need to eat, sleep, take a break or spend time on morning ablutions and whatnot. Best of all, robots don't even demand a salary or better working conditions. In short, the reliability of a robot simply cannot be matched by even the best human employees.

Robots and drones are not the only heroes taking supply chains to new levels - self-driving vehicles are the new stars on the block. But a flashback is required to put matters in perspective and clarify how AI benefits humanity, rather than being perceived as an inherent threat that could soon enslave the human race, as some analysts fear.

During the past two-odd centuries, men and machines have been working in tandem, seeking to boost the comforts and conveniences of the human race. Yet, the first form of genuine mass production only occurred when Henry Ford introduced the assembly line in 1913. Thereafter, the first moves towards greater mechanization and automation began gathering pace, although 'automation' as a term only emerged in 1946.

In its formative years, though, automation was primarily allied with manufacturing. The advent of the digital age, however, has imparted a new dimension to this term. The widespread use of computers has led to the creation of integrated circuits and a shift towards miniaturisation in almost all domains. Small is now big. Nanotechnology has taken this to new orbits altogether. Consequently, automation received a boost because even as performance and production grew exponentially, timeframes and costs dropped. Calculations and deductions that may have taken humans hours, months or years are now being done by artificially intelligent computers within seconds.

What automation had done to speed up repetitive tasks is now playing out in the analysis of big data via the use of artificial intelligence. Human hands had been replaced long ago. But not many would have foreseen human minds being replaced. Welcome to the world of artificial intelligence!

Presently, AI in SCM also manifests as robotics process automation or RPA. Here, software robots manage "clerical process automation technology". This is not restricted to physical systems alone but integrates various ones dealing with overseeing and implementing orders. RPA automates end-to-end supply chains, facilitating management of varied tasks and domains in the proper cycle. With RPA, managers can devote minimal time to daily activities and processes that are frequent but of low value, spending the extra time on high-value tasks garnering greater revenues for the business.

As per PwC estimates, about 45% of present workforce activities could be done by self-automated machines, saving around $2 trillion annually for the companies in question. Besides cost savings and efficiency improvements, PwC adds that RPA could drive businesses to their next level of optimal production. This is already evident in Amazon's operations where robots manage daily operations.

Boosting End-to-End Logistics

Robotics apart, the other big advantage of AI lies in end-to-end logistics, which includes autonomous or driverless vehicles. Using AI, online orders placed hours earlier could be delivered the same day. AI oversees and connects the dots between suppliers, manufacturers, wholesalers, retailers and end customers.

In India and abroad, there are companies that specialise in offering end-to -end logistics solutions for SCM. Such companies design, assemble and market autonomous and driver assistance software and systems for commercial automotive and industrial applications. To enhance automotive applications, there are devices that boost driver awareness, apart from providing partial, conditional and full autonomy. To promote industrial applications, such companies provide autonomous mobile robots for end-to-end warehouse logistics.

As e-commerce and digitalisation gain pace worldwide, the rise of AI in manufacturing, warehousing and logistics will keep growing by the day. Industry estimates indicate that by 2025, there will be a $185 billion market for Advanced Driver Assistance Systems (ADAS) and Industrial Logistics Robotics, growing at 21%+ CAGR from $39 billion in 2017. The benefits of using AI in logistics include an increase in asset utilisation; preservation of natural resources; risk reduction; time and cost efficiencies; and a decrease in pollution, among others.

ADAS and AV (Autonomous Vehicle) systems include features such as co-pilot warning system, driver profiling, predictive analytics, forward collision /lane departure warning, vulnerable user detection, emergency brake assist, lane keep assist, adaptive cruise control with automatic steering, HD (high -definition) maps and 3D reconstruction.

Driverless vehicles would be the norm in supply chains of the future, which will be supported by the Internet of Things (IoT), Cloud Computing and Big Data Analytics. The integrated supply chain journey will begin from the cluster of suppliers, connected with integrated manufacturing systems in the manufacturer's plants through the IoT. Once orders are received online, supplies will be moved seamlessly via driverless vehicles to the plant. Here , mobile robots will undertake tasks.

The finished goods will then be loaded onto driverless vehicles by robots and transported to smart warehouses. Thereafter, the consignments will be categorised and shipped to retailers through driverless vehicles or sent directly to the clients. The last-mile connectivity to customers would also be through autonomous or driverless vehicles but with a delivery executive on board for handing over the ordered parcel to the customer. The entire details of the integrated supply chain transaction would be stored in the Cloud, available for future reference when required.

In almost the entire transaction, AI would manifest in some form or the other - computers crunching supply data, driverless vehicles shipping the consignment from supplier to manufacturer to warehouse to customer, mobile robots then transferring the consignment from plant to driverless vehicle, which would then be transported across the last mile to the customer's address.

AI will also be seen in autonomous mobile robots and self-driving forklifts and pallet jacks for material flow in manufacturing plants and warehouses. The GPS-enabled driverless vehicles would permit nonstop tracking of the shipment in real-time, pre-empting any chances of pilferage and idling or wastage of time that is common with human drivers.

In this end-to-end logistics supply chain, multiple benefits abound for end users. Partial or complete autonomy of vehicles will ensure a reduced number of accidents and higher driver safety. There will be cost savings related to eliminating or minimising accidents, coupled with enhancement in the driver's wellbeing. Fuel savings and enhanced efficiency will comprise the additional benefits. The final benefits would include the ability of the company to run lean operations at minimal labour cost, thereby prolonging the life of its assets.

Path to Full Automation

The levels of automated driving range from L1 to L5. L1 offers driver assistance. L2 has partial driver assistance. L3 refers to conditional automation. And L4 denotes high automation while L5 is full automation. At this juncture, autonomous vehicles up to L4 are deployed in India.

Currently, completely autonomous vehicles have not yet come on the roads, except for test drives. Nor do present road regulations permit L5 driverless vehicles in India. Nonetheless, L4 autonomous shuttles are allowed within gated precincts where the regular road or pedestrian traffic is not present. These include large office campuses, elderly care communities, Smart Cities, trade fair and theme parks, among others. Such L4 shuttles are capable of autonomous route planning, autonomous emergency braking and reactive manoeuvres, Cloud-based fleet management and on-demand ride calling using a mobile app.

Till full autonomy arrives, it is imperative that partially-autonomous vehicles are allowed to operate on the roads since this can potentially save many lives that would otherwise be lost due to driver error or unsafe driving. The safety quotient is enhanced by features such as forward collision and lane departure warnings, parking assistance with rear camera and lane-keep assist, highway and city autopilot modes, among others.

In this stage too, AI has a role to play through the Co-Pilot System whereby the driver's alertness and drowsiness levels are monitored, including distracted driving, even while the vehicle is cruising on Autopilot. The system also offers complete driver profiling and predictive analysis, enabling safe driving behaviour by predicting unsafe habits.

Moreover, 3D LIDAR (Light Detection and Ranging) monitors the surroundings. A remote-sensing system, LIDAR's computer-vision technology checks to ensure there are no objects or obstructions that can pose a threat. The data is then transmitted to the onboard computer, which helps it decide whether to continue cruising or to accelerate, brake or switch lanes to the right or left. As AI technology advances in the future, it will be possible to convert existing vehicles to self-driving ones. Besides the benefits already mentioned above, safety aspects and low maintenance are the other advantages . All this should drive faster, timely deliveries and complete customer satisfaction - precisely what supply chain management is all about.