Industry 4.0: AI in Logistics and Supply Chain

The fourth industrial revolution has changed our thinking of how an ordinary world can be into something which was thought to be impossible until two decades ago.

The primary focus is the automation of existing technology and technologies like artificial intelligence (AI), machine learning, deep learning, the Internet of Things (IoT), etc. Siri and Google assistant are classic examples of using these technologies, which impacted people on a global scale. Earlier, going to a library nearby was the only solution to gather some information on any topic. The answers they need today are just a google search away. The question remains as to whether a robot can do all the work a human can do. With the momentum at which AI is developing, robots replacing humans would not be as far as we think it would be.

AI has come a long way since the 1950s, and almost 90 percent of human beings use it daily. As it aids humankind, it is beneficial for  MNCs, small and medium-scale enterprises. Amazon employs a flywheel AI strategy.  It is a tool that is used to store rotational energy efficiently. It is mainly used when a machine does not produce constant energy that is enough to work. When the machine has an irregular energy supply, this tool uses rotational energy to make sure that the device gets enough power. The company makes sure that the technology they create covers every nook and corner of their offices globally. This strategy makes sure that Amazon is efficiently making use of its technology to make everything easy for its customers. 

Machine learning and AI go hand in hand. Machine learning helps us to predict demand and forecast the analytics based on datasets acquired by the company and the users. AI helps us optimize the route for logistics, which will eventually reduce shipping costs. Logistics is one industry where AI seems to have made the work more efficient and effortless. The logistics industry is a data-driven world. Machine learning and AI have helped it acquire data and optimize processes more efficiently in productivity terms and monetization terms. This industry receives an ocean of irregular and patternless data, which creates billing information, customer addresses, date and time of order and delivery, etc.

When a particular company requests the information of a specific customer but is unclear of certain details, it will be a grueling task for a single human being to access that information in a short amount of time. It may even take days to search for specific data from numerous datasets. This is where companies think AI plays a vital role. AI can locate the information in just minutes and make it accessible to the companies that requested the data directly.

Automated warehousing is one of the most imperative applications of AI in the logistics industry. Warehouse automation fundamentally means processes like inventory management, data collection, etc will be automatically and efficiently implemented with the help of AI. An automated warehouse uses AI to predict customer and industry demands way before the actual numbers arrive, which therefore leads to proper planning of orders and logistics. Due to this process, companies now have more efficient handling of the routes and handling the warehouse. Ocado, a supermarket in the United Kingdom, has successfully developed and implemented an automated warehouse. They use a system called the hive-grid machines where the robots in this system can process and execute up to 65,000 orders in a week. These robots move, lift and sort items according to the demand of Ocado. The whole process of automation has resulted in a significant labour cut and a more time-efficient method. 

However, is this is an efficient process?

There are two schools of thought—the first one from a business perspective. The main objective of a business is to maximize profit and annual turnover as much as possible with low investment. When a labour is appointed in a warehouse, the company has to take care of the training cost, incentive, and sometimes eventhe travel costs and basic needs. The total labour cost for a company is around 60 percent of the warehouse’s total cost, excluding shipping costs. Naturally, a business person will think that automation is a one-time investment with a high chance of high annual turnover. But all these come with a hefty price to pay.

Here are some rough estimates of the cost of automating the average warehouse:

  • Fully automated solution — at least $25 million
  • Semi-automated solution — between $5 – $15 million
  • Mechanized solution — $1 – $5 million
  • An automated solution that improves manual picking activities — between $500,000 and $1 million

The second school of thought is the humanitarian side of this so-called efficiency. One of the major risks faced by the labourers of the logistics industry will be unemployment. A big chunk of labourers working in the logistics industry does not have the skills to operate or work with an AI-aided robot. This forces the employer to fire the existing employees and find new and skilled employees capable enough to handle a robot. Job loss to automation statistics indicates that 71 per cent of the total task hours are now completed by humans and machines meet the remaining 29 per cent. In four years, the percentage of total task hours completed by humans will become 58 and 42 per cent completed by machines. 

How far along is India concerning the same?

AI possibly will add 15 per cent to India’s current gross value in 2035. With the use of technology increasing day by day, India is currently not able to implement a full-fledged AI-aided logistics industry. The Indian logistics sector employs about 21.24 million people as of 2016. With AI, this number has the potential to be reduced nearly by half. The demand for skilled workers is on the rise constantly. Even if companies plan on automating their processes, they should undertake step-by-step planning so that it does not affect the lives of its labourers. “Cobots” or collaboration with robots is an excellent way to get the process started. Companies can begin recruiting skilled people and train them to work with robots and professionally handle them. However, ultimately, there has to be a human in every step to ensure a flawless process. It is a long road ahead before the industry becomes a fully automated industry.