Artificial Intelligence (AI) is an emerging digital technology-driven tool to support various processes from design and development to distribution and delivery of goods and services with improved quality, safety, security and punctuality, thereby helping to enhance consumer satisfaction and boost the trust-building process. Since there is no artificial or arbitrary element in it and the level of intelligence is enhanced in this programme, I call it Augmented Intelligence. Packaging and labelling, being an integral part of the products, are also transforming by adopting such contemporary technologies to remain at par with the industry standards across the globe.
AI is a hybrid form of programming, which is built on numerous micro-level data and various information with multiple in-built logics. It is a customised intelligent program and can be compared with a cluster of PLCs, where multiple logics are used for processing and analysing data and information to take a decision or an action. Often various machine learning data are also ingrained for AI programming to make it suitable for controlling different equipment and their functionalities. Ergonomic and demographical data derived from human nature and behaviour are also used to develop multiple logics for analysing data internally. All these help to behave the program as close as the human brain, but in a much quicker and smarter manner, eliminating subjectivity and variability. AI has inputs from multiple processes, data from various unit operations and a lot of logical information which helps to make rational decisions and appropriate actions, mimicking the human brain. The critical part of human intelligence is reasoning or judgement-based decisionmaking and actions. This is quite natural or spontaneous and varies from person to person depending on individual intellect, wisdom and many external factors. Since the level of understanding, reasoning and intelligence varies from person to person, the quality of judgement also varies while making a decision or taking an action. Secondly, the time spent to take a decision or an action varies from person to person because of this difference in level of understanding and intelligence. It also varies from time to time depending on individual physical and mental status and a set of external factors. Perception, understanding, interpretation and reasoning varies from person to person along with their rational and analytical capabilities.
AI is developed for maintaining consistency with quality and swift actions with rational decisions to mitigate this risk of variability and to eliminate the human factor, especially in large scale processes and operations. AI primarily works on data, information and logic, something similar to our mind which works on thoughts, feelings and emotions. Our decisions and actions are derived from our thoughts, feelings and emotions which is the result of internal churning within our minds. Developing an AI programme is a complex process and data is one of the critical ingredients to develop it. Data capture, data transform, data storage, data processing, data analysis, data transfer, data exchange to data retrieval all are part of the programme and primarily responsible for its functionality. Hence data hygiene and data integrity are very much essential for its effective functioning. The same is true for the information and logic, which should be authentic and rational for the successful development and functioning of any AI programme.
Even though packaging and labelling are widely spread across various industries to protect the product and secure its stability, quality and safety across the entire supply chain, the majority of it is still under the MSME sector and often most of them cannot afford a costly and complex tool like AI in their operations. However, packaging and labelling users (relatively larger industry houses) can explore a few areas to optimise the productivity and quality of their goods and services. The major role of packaging and labelling is brand protection and brand promotion, establishing connectivity of the product with the people and supporting the entire operation and supply chain system. There are a few areas where AI programme can be customised to deploy in optimising the packaging design from primary packaging level to palletisation. It can also help to enhance productivity, minimise process cycle time, improve accuracy and maintain consistency. It is also helpful for quality and regulatory compliance.
During the packaging design and development phase, AI can help select the right container closure system (primary pack) or a better pack option with optimum volume and maximum level of protection. Similarly, it can also help in optimising dimensions of secondary and tertiary packs to maximise pallet capacity. It can also help in designing the packaging process through process mapping with minimum floor space utilisation and process cycle time. However, to develop the program a lot of product data, packaging material data and data from each unit operation will be required, along with other allied information to analyse internally for an optimal workable option through its built-in logics.
AI can also help in standardising, harmonising and optimising material specifications and process parameters for consistent results through automation, wherever feasible. Artwork and Artwork Management System (AMS) are part of labelling which is an integral part of packaging. Nowadays these are mostly being managed digitally for speed, accuracy and quality. The entire AMS can be well managed through AI to eliminate variability across multiple sites of operations. AI can also help in managing a large volume of work with multiple languages for any global business. Generic updates, applicable to multiple product labelling, also can be managed well through an AI program. Checking of artworks, proofs and commercial supplies of printed packaging materials can also be automated through AI tools. A well-programmed AI can also manage local and regional languages along with a common global language and its translation as per the end user’s requirement.
Digital features on labelling, coupled with AI tools can change the entire landscape. Quality function associated with packaging materials, packaging operations and finished packs can also be considered for managing through AI tools to minimise or eliminate variability due to human factors. This can result in uniform quality of a product pack while reaching the end users. AI can also be deployed in areas like rejection analysis, process control, demand-supply management, forecasting, scheduling and planning, warehouse management, vendor management, etc. However, before deploying AI for any process, basic data, information and logics need to be made part of the URS for the successful development of the program. We have seen the growth of the pharma industry from small scale manual operations to large scale automated operations to cope up with the business need and speed. Application software like ERP / SAP, TRACKWISE, DOCUMENTUM, LIMS, and GLAMS / AMS are now integral parts of a globally successful pharma business. Similarly, AI also will make inroads in coming years and become an integral part of the process. Even though AI has the potential to bring transformation in every level of our society, thoughts, feelings and emotions are still in the precious possession of human beings and that is why people are continuously working on various advanced tools to enhance the quality of goods and services to satisfy our necessities.