Ripon Kumer Sarker-
Artificial intelligence (AI) will put many out of jobs. But at the same time, it will create new jobs for many. AI will inevitably play a significant role in every aspect of our lives as a result of the evolution of new technology. The top leaders of G7 countries recently agreed that controlled AI integration should be adopted. ChatGPT and Google’s Bard have been very popular worldwide among general people.
With the use of AI, the industry is undergoing a significant transformation. The Covid-19 pandemic has drastically changed the world, and this has made it more difficult for global supply chains to operate. The supply shock originating in China in February 2020 and the subsequent demand shock has laid bare vulnerabilities in production strategies and supply chain networks worldwide. Temporary trade restrictions and manufacturing supply shortages have starkly illuminated weaknesses in these systems.
Compounded by the US-China trade war and recent conflicts such as the Ukraine-Russia war, economic nationalism has surged, creating an even more complex landscape. To navigate these challenges, manufacturers worldwide are facing mounting pressures to increase domestic production, foster local employment, reduce dependence on risky sources, and reimagine lean manufacturing strategies. However, amidst these transformations, the demand for low prices, fierce competition, and the drive for operational efficiency remains steadfast. In this rapidly evolving environment, the role of AI emerges as a vital catalyst for unlocking the true potential of warehouse and supply chain management.
The integration of AI into warehouse and supply chain management effectively addresses the pressing needs of the post-pandemic era. Foremost, it empowers manufacturers to bolster domestic production capabilities, reducing their reliance on fragile global supply chains. By deploying AI-powered solutions, businesses can optimize production planning, streamline logistics operations, and enhance inventory management. These advancements enable the creation of agile and responsive supply chain ecosystems capable of withstanding unexpected disruptions.
Mr. Mesbah Uddin, a US-based Bangladeshi data scientist, is an expert in data-driven solutions for manufacturing and warehouse operations. Currently, he is working in a company where he has to deal with thousands of products from inventory management to final delivery among the vendors. In a recent interview with Mr. Uddin, he expressed with his deep knowledge of machine learning and artificial intelligence that these technologies hold the key to efficiently addressing the challenges in this field.
Specific Applications of AI and Machine Learning Tools in the Warehouses
AI and machine learning tools have specific applications in warehouses that significantly enhance operations and efficiency. One crucial area is accurate inventory management, which ensures a smooth flow of items in and out of the warehouse, preventing issues such as overstocking, inadequate stocking, and unexpected stock-outs. However, the inventory management process involves multiple variables, including order processing, picking, and packing, which can be time-consuming and prone to errors. AI algorithms and data analysis capabilities enable companies to make informed decisions about inventory, optimizing stock levels and preventing overstocking, inadequate stocking, and unexpected stock-outs. By automating the inventory management process, AI reduces manual effort, minimizes errors, and saves time and resources.
Another application is optimizing delivery truck routes. AI can analyze delivery data, predict traffic patterns, and recommend the most efficient routes for delivery trucks. This reduces time spent on the road, improves delivery times, and minimizes the risk of delays.
Additionally, AI systems offer benefits across the entire supply chain, from customer service to the warehouse. Automated intelligent operations reduce human oversight errors and workplace incidents, resulting in error-free processes and improved safety. AI-powered warehouse robots can operate with incredible speed and accuracy, leading to higher productivity and reduced operational costs.
Challenges of Using Those Tools in a Warehouse
AI systems require high-quality and diverse data to function effectively. In a factory collecting data from various sources, such as inventory systems, sensors, and logistics software, can be challenging. Also, the integration of AI into the existing infrastructure can be challenging. Warehouses deal with dynamic environments where the volume and nature of operations can change rapidly. Scaling AI solutions to accommodate growing volumes and adapting them to evolving business needs can be complex. On top of that, introducing AI tools into a warehouse necessitates the training and upskilling of the existing workforce. Employees may need to learn how to operate and interact with AI systems effectively. Again, total AI systems deal with thousands of sensitive data which are assets to the company. Ensuring robust security measures to protect against cyber threats and unauthorized access is critical.
Tackling the Challenges
When asked about the solution to these challenges, Mr. Uddin said, “The recent advancements in machine learning and artificial intelligence have led to the emergence of various popular algorithms. Researchers and scientists are actively working on developing models that can effectively work with limited data. One example is the reinforced model which was used in ChatGPT. I am currently working on a new reinforced-based data framework model that can generate new historical data sets”. By starting with a model that has learned general patterns, the need for a large amount of domain-specific data is reduced, and the model can be adapted to the specific warehouse operations – he added.
Active learning among the existing workforce, knowledge transfer on AI, training of AI models on simulated data, synthetic data generation, and continuous improvement will tackle the challenges effectively.
Prospects of Those Tools in the Future of the Warehouse Industry. Will It Stay Forever?
“Speed in decision-making, speed in reducing cycle-times and speed in operations”. The integration of AI in the supply chain is set to revolutionize decision-making, cycle times, operations, and continuous improvement. Its impact is projected to be significant in the years to come, with supply chain organizations expecting a doubling of machine automation within their processes over the next five years.
Additionally, there is a forecasted growth in global spending on Industrial Internet of Things (IIoT) Platforms, reaching a compound annual growth rate (CAGR) of 40 percent from 2018 (1.67 billion US dollars) to 2024 (12.44 billion US dollars). In today’s digitally connected world, industries across the board prioritize maximizing productivity and minimizing uncertainties.
The demand for supersonic speed and operational efficiencies further emphasizes the need to harness the power of AI in supply chains and logistics. By leveraging AI, supply chain organizations can enhance decision-making processes, enabling faster and more accurate responses to changing market dynamics. AI algorithms and predictive analytics assist in reducing cycle times by optimizing routes, inventory management, and demand forecasting, resulting in streamlined operations and improved efficiency.
Ripon Kumer Sarker is an Engineer and Supply Chain Management Professional
