The manufacturing sector in India is warming up to the digital and automation revolution, especially after the COVID-19 pandemic played havoc with the supply chain so essential for the manufacturing industry. This disruption forced the industry to rethink the way they do business by adopting newer technologies such as automation, interconnectivity, AI-ML, and real-time data exchange capabilities.
These technologies enable the manufacturing industry to perform and sustain their day-to-day operations, along with the optimal usage of man, machine, and money.
Supply chain challenges
Supply chain refers to activities in business operations that cover procurement, production planning and scheduling, inventory management and tracking, demand forecasting, as well as distribution and logistics.
These areas have faced problems such as higher costs, variations in demand and supply, piling or stock out, and logistical and monitoring challenges. Variation in supply chain activities result in either under or overbuying of materials, leading to incorrect planning and cash flow projection.
To mitigate these challenges, the industry is now embracing new digital interventions that can help them in areas such as optimization of procurement, automated job scheduling and monitoring, automated inventory, and warehouse management.
After the pandemic, industries have set themselves on the path of sustenance to growth. One of the focus areas has been intelligently planning the supply chain. Technologies helping to do so in this area are depicted below.
In order to achieve this along with factory automation and safety enablement for the workforce, the major focus will need to be on intelligently planning the supply chain areas. This will involve organizations having the ability to:
Companies are looking to establish a connected platform to integrate the internal operations and their business process. This interlocking will help them abolish the fragmented view of the operations and will enable them to visualize and adjust to the demands quickly and efficiently. Automated planning and scheduling will support this activity. When combined with MES, it can provide a unified view of the factory operations, which impacts the supply chain operations. Implementing geo-tracking solutions can help organizations understand the position of vehicles in transit.
Here are three specific operational areas that can be transformed using data analytics, AI, and automation.
Develop forecasting ability to streamline demand and supply: Data analytics and artificial intelligence play a large role in the ability to forecast demand and make quicker decisions to respond and synchronize according to the supply chain network. These technologies can be used to develop mathematical and predictive models that can predict future demands considering historical data.
Establish logistical control tower: Creating command center and logistical control tower will help establish a visual relationship between the manufacturing plant, suppliers, logistics partner, and customers. The command center may connect to back-end systems that are managing fleet, suppliers, etc., and provide business process indicators.
Automating warehouse management system: Modern warehouse management solutions can minimize errors in inventory tracking. Integrating the same with other manufacturing systems (such as MES) will give a clearer picture of inventory consumption and help rationalize the operations.
The supply chain disruption caused by the pandemic has helped all industries, especially the manufacturing industry, draw lessons on how to sustain and survive amid uncertainty and disruptions. The industry is now keen to adopt technologies such as:
Factory automation powered by industrial IoT
Integrated production planning and scheduling
AI-driven demand and supply chain planning
Remote monitoring and AI-driven decision support systems
Connected products and servitization
These technologies enable enterprises to rationalize their operations, reduce costs, and increase operational efficiency.