The consumer packaged goods (CPG) manufacturing industry is undergoing rapid, fundamental changes. On the demand side, manufacturers face a market that has shifted sharply towards digital, on-demand and online experiences. This has led to increased demand volatility, and requires shorter lead times for fulfilment. On the operational side, manufacturers now have an array of new tools and opportunities to adopt, which can radically improve their processes for addressing demand challenges. These include digital transformations enabled by internet of things (IoT) as well as new operational efficiencies offered by new-age technologies such as artificial intelligence (AI) and robotics.
In order to adapt to an ever-accelerating technology transformation, CPG companies must expedite product innovation and build flexible, resilient supply chains that can weather disruptions and swiftly introduce new products to the market. According to a recent study, conducted by Rockwell Automation, comprising a survey of 216 CPG leaders across 13 leading manufacturing countries, 78 per cent of respondents believe that switching to smart manufacturing is crucial for the success of their businesses in the future. Moreover, 49 per cent of respondents have already adopted smart manufacturing, while another 45 per cent say that they will adopt it within a year.
A look at the key digital trends dominating the CPG manufacturing space and the way forward…
A connected plant is one that links its physical assets or machinery under management with operators in the functional areas of production, efficiency, security and safety of the equipment and products. In essence, it utilises modern technologies to improve the value of the final product through collaboration. Manufacturing enterprises are actively implementing advanced automated solutions to connect machines and workers 24×7, monitor equipment performance and determine the overall equipment efficiency (OEE). This is made possible by establishing connectivity with assets, machines and control systems, and by leveraging emerging technologies such as big data, cloud, mobility, application programming interface-based integration, microservices, and AI and machine learning (ML) algorithms. Connected plants can integrate various applications such as plant historians, plant manager dashboards, industrial IoT platforms, daily work management and analytics workbenches. All these applications operate in synergy, along with a range of new Industry 4.0 technologies such as advanced automation, autonomous vehicles, new-age and collaborative robots, augmented and virtual reality, digital twins, 3D printing, and radio frequency identification.
Connected plants enable plant operators to remotely connect from any location to assess product quality, analyse productivity, monitor machine performance and make data-based improvements. This enhanced connectivity between workers and machines in a connected plant environment significantly reduces downtime. Additionally, OEE visualisation integrates disparate information technology and operational technology data, to offer valuable insights into plant performance, plant availability, quality of equipment and manufacturing lines. Fault alerts and early alarms also help operators identify and focus on the most critical plant issues, thereby reducing diagnostics time.
The growing adoption of IoT in industrial applications integrates every element of the manufacturing process, making it function as a cohesive single entity, which is commonly referred to as the smart factory. IoT sensors capture data on product specifications and other metrics. Manufacturers can utilise devices equipped with IoT sensors to capture and monitor real-time data on all their assets through web or mobile applications. These tracked assets can include vehicles that deliver raw materials or produced goods (fleet management), items in warehouses (inventory management), or resources utilised during the production process. They can track and optimise assets at every manufacturing stage, from the supply chain to the end-product delivery. Effective asset monitoring enables quick and efficient identification of issues that could otherwise adversely impact the product quality or time-to-market. IoT-enabled manufacturing, thus facilitates streamlined business operations, optimised productivity and improved returns on investment. IoT applications in a CPG set-up manage a whole range of functionalities, from data-driven coolers that intelligently manage beverage shipments to sensor-carrying packaging that tracks inventory and streamlines supply chains.
The next few years will present significant opportunities for CPG enterprises looking to expand their operations. According to Amazon Web Services, the market for smart packaging alone is set to reach $61.91 billion in less than five years, at a compound annual growth rate of 5.87 per cent from 2021. However, the shift from traditional supply chain management strategies to integrating IoT technologies is not a linear move. Capturing the benefits of IoT systems requires large-scale investments, along with a thorough understanding of the company’s current supply chain scenario to align its operations and achieve the desired outcomes in the future.
Automation and robotics
Automation technologies, combined with advanced analytics, help to effectively reduce risks and overhead allocation costs, and improve OEE and operating margins. Automated devices allow employees to fix various performance issues through virtual networks, eliminating the need for physical manpower, thereby achieving effective management and control of the equipment. Virtual equipment monitoring also enables employees to know the device location, including movable assets. Automating movement and handling of in-factory materials and equipment offers several benefits, such as directly reducing the number of workers by decreasing the need for forklift operators and other human-driven transportation operations. It also reduces the need for people handling raw materials and packaging, thereby minimising the risk of contamination of ingredients and finished products. This will reduce risk and improve food safety. Many CPG enterprises are increasingly adopting automated processes for in-factory transportation, such as the utilisation of autonomous indoor vehicles that move materials and goods between warehouses and production lines. CPG companies are also embracing robotics as a tool to automate production, storage and distribution processes. Deployment of automated, guided vehicles, industrial robots, collaborative robots and mobile robots helps to effectively address problems of labour shortages and facilitates flexibility on the production line. With the use of robotics, CPG companies can automate repetitive tasks, increase speed and productivity, achieve consistent product handling, improve operator safety and minimise human error. As enterprises start preparing their production workflows to incorporate robotics, the adoption rate of this technology in CPG manufacturing is expected to rise.
AI is a powerful tool with the potential to transform various aspects of the CPG sector. An AI-compatible smart plant can enhance the overall industrial production system by forecasting delays, managing inventory/tracking stocks, anticipating delivery speed and providing the highest quality goods to consumers. ML-based predictive analytics enables manufacturers to assess vast amounts of historical and real-time data to generate accurate demand forecasts. In addition, prescriptive analytics can recommend optimal courses of action based on generated forecasts. AI-powered solutions enable automation of processes such as quality control testing and product inspection. Advanced AI algorithms in deep learning and artificial neural networks are used for repair prediction and formulation of accurate asset failure predictions.
The digital twin technology leverages all other advanced technologies such as IoT, AI, ML and cloud. Digital twins, which are virtual replicas of physical objects, can yield potential benefits when applied on the manufacturing floor. With the use of virtual copies of equipment and spare parts, workers and managers can simulate a number of processes, conduct experiments, identify issues and achieve desired results without risking or damaging physical assets. Four key technologies are needed to develop and deploy digital twins at scale – data from physical systems, IoT connectivity, modelling methods and at-scale computing. Each of these technologies has been developed in parallel over the past few years. More recently, they have converged to enable the implementation of digital twins at scale in the CPG industry.
The primary benefit of digital twins in CPG manufacturing lies in their ability to automatically provide comprehensive information about equipment or product performance without manual intervention. Given the current computing capabilities, factories can quickly analyse the data provided by the physical twin, using advanced ML algorithms, and convert it into actionable insights. Prior to the inception of digital twins, such a level of performance management and control in manufacturing was practically unattainable.
Adoption roadblocks and future outlook
While technological advancements are demonstrating tangible efficiencies, there are still stumbling blocks to adopting advanced solutions across the CPG industry. The primary obstacle to adoption is the high costs involved in the deployment of these technologies. However, the shift from traditionally operated factories to IoT-connected, IP-based systems also exposes them to new cybercrime vulnerabilities. Each point of connection becomes an added risk for potential attacks and cybercrimes, which can lead to interference, unauthorised remote access, intellectual property theft and data loss. Other challenges include incompatibility issues with legacy systems and a lack of technical knowledge and skills among workforce to use these technologies. Nevertheless, given its benefits, there seems to be a distinct interest in adopting smart manufacturing in the near term. CPG businesses are embracing an incremental lower-initial-cost and resource approach to smart manufacturing and connected plants by adopting modular solutions that provide a strong value and quick payback time.