CXOToday has engaged in an exclusive interview with Arvind Kakru, Director Sales, Rockwell Automation India
- What is the role of digital automation in improving efficiency in supply chain management?
Manufacturing companies are experiencing disruptions to their supply chain and manufacturing operations like never seen before. In an intertwined global environment, factories and shipping locations will be at risk in some shape or form. And no matter what products and services companies produce, the new normal is likely to impact those products and services, potentially even making them obsolete. It is critical for companies to assess and adapt quickly to changing market demand and thus position themselves for success.
A business’ end-to-end supply chain practices must be agile enough to make faster changes, and resilient enough to recover from a lack of raw materials, products, or capacity. Agility will ensure the right cost, service, and quality given external market factors. Resilience will mitigate the impact of disruption where there are potential points of failure. From an agility perspective, the convergence of Information Technology (IT) and Operations Technology (OT) fits into an overall digital manufacturing strategy. A digitally transformed organization is faster to the right decision and can more easily achieve the right balance of agility and resilience in the supply chain.
Advanced digital enablers can help businesses boost visibility, reduce risks, and improve efficiency via technologies such as the Internet of Things (IoT), advanced analytics, Manufacturing Execution Systems (MES), and moving to Software as a Service in the cloud. Manufacturers can tap on supply chain planning and management digital tools to dynamically plan in near real-time, optimize, and better sync with suppliers to ensure that the right inventory is available at the right time to meet customer demands. Some significant use cases around Intelligent asset optimization to workforce productivity and enterprise operational intelligence and Augmented Reality are key to the larger digital transformations. Sustainability is another focus area that will be a differentiating factor for manufacturers using digital tools across supply chains.
- How are the trends of supply chain management expected to shape the manufacturing sector in the digital era?
The digital era is transforming supply chain management and manufacturing in several ways. Advances in robotics, automation, artificial intelligence, and machine learning are driving greater efficiency in manufacturing. This means that more tasks will be performed by machines, which can increase efficiency and reduce costs. Digital technologies are enabling manufacturers to offer more customized products to customers. This is because digital tools can help companies design and produce products more quickly and with greater precision. Digital technologies can provide real-time visibility into the supply chain, enabling manufacturers to track the movement of goods and monitor inventory levels.
Companies can make better decisions about production and shipping schedules, which can reduce inventory costs and improve customer service. Better collaboration between suppliers, manufacturers, and distributors is possible using these tools and technologies. They can build stronger relationships, reduce communication errors, and improve overall supply chain performance. Consumers are increasingly concerned about the environmental impact of products. Manufacturers are responding by adopting sustainable practices and technologies, using digital tools.
Overall, the trends in supply chain management are expected to shape the manufacturing sector by increasing efficiency, improving collaboration, and enabling greater customization and sustainability. Companies that can adapt to these trends are likely to be more competitive and successful in the digital era.
- What are the key use cases of new-age technologies such as AI, IoT, and AR/VR? How are you leveraging these solutions?
Artificial Intelligence (AI) and Machine Learning (ML) are disrupting industrial manufacturing. Today, we are seeing growing interest in the democratization of AI and ML in the industrial manufacturing space. Manufacturers are engaging stakeholders with a range of domain knowledge to contribute toward better analytics initiatives. The adoption of Internet-of-Things (IoT) solutions is immense, it’s key to prioritize opportunities and applications that will help realize early returns on investments while creating the right foundation for longer-term growth and success.
Companies today are challenged with the biggest workforce shortage in decades which has manifested into a skills gap never witnessed in manufacturing. Digitally native, early-entry employees are looking for innovators in technology to achieve productivity rapidly. Industrial Augmented Reality (AR) can help improve workforce productivity, efficiency, and safety, all while enhancing customer satisfaction.
New digital innovations, applications, and solutions can enable significant improvements in manufacturing performance and business outcomes in five key areas:
- Assets and operations: Management and control of equipment and systems within a given operating environment.
- Resources and environment: Focused on the resources utilized and consumed conducting operations as well as environmental systems and management.
- People and processes: Deal with the impact of operators, skilled technicians, and support personnel on operations.
- Materials and supply chain: Focused on the information, and resources involved in providing the raw materials and components required in production.
- Enterprise integration: Focused on linkages and integrations with the information and resources within the enterprise that require interfaces to/from to support production.
In the above areas, Rockwell Automation has a set of products and solutions that optimize asset efficiency, reduce machine downtime, and increase throughput to satisfy customer demand. Manufacturers have also used our solutions to drive enhanced visibility, and sustainable operations and solve complex business problems.
- What are your views on the future of supply chain optimization with ChatGPT and other AI techniques?
AI techniques have a significant role to play in the future of supply chain optimization. AI techniques, including natural language processing, machine learning, and predictive analytics, can provide insights and recommendations that can help improve supply chain efficiency and reduce costs.
AI techniques can analyze large amounts of data to identify patterns and make predictions about future demand, inventory levels, and supply chain disruptions. This can help companies optimize inventory levels, reduce waste, and improve customer service. AI techniques can process input from customers, suppliers, and other stakeholders to provide real-time responses and recommendations. This can help improve communication and collaboration within the supply chain. AI techniques can learn from past supply chain performance to identify opportunities for improvement and suggest actions to optimize performance. This can help companies make better decisions and improve overall supply chain efficiency.
Overall, the future of supply chain optimization with AI techniques looks promising. By leveraging the power of AI, companies can gain deeper insights into their supply chain operations, improve decision-making, and achieve greater efficiency and profitability. However, it’s important to note that AI is not a silver bullet, and it should be used in conjunction with human expertise and critical business objectives to achieve the best results.
- Do you foresee any challenges brands will deal with because of AI-based supply chain automation?
While AI-based supply chain automation can bring many benefits, there are also some challenges that brands may face.
AI-based systems require high-quality data to function effectively. If the data is incomplete or inaccurate, the AI system may make incorrect predictions or recommendations. Implementing AI-based supply chain automation may require changes to existing processes and systems, which can meet with resistance from employees who are used to working in a particular way.
As supply chains become more connected and digitized, they may become more vulnerable to cyber-attacks. Brands will need to ensure that their AI-based systems are secure and resilient against such attacks. The development and deployment of AI-based systems may require specialized skills that are currently in short supply. Brands will need to invest in training and recruiting talent with these skills to ensure the success of their supply chain automation initiatives.
As AI-based systems become more powerful, they may raise legal and ethical concerns around issues such as privacy, bias, and accountability. Manufacturers will need to ensure that their AI-based systems are transparent, ethical, and compliant with relevant regulations.
Overall, while AI-based supply chain automation can bring significant benefits, brands will need to carefully consider these challenges and develop strategies to address them effectively. This will require a combination of technical expertise, organizational change management, and a focus on ethical and legal considerations.
