We have seen ERP and Non-ERP software systems for managing Environment, Health and Safety processes. Those offering excellent business process management systems to manage all the spectrum of EHS and compliance processes. With the advent of Digital Technologies and COVID-19 like scenarios, such software systems have shown definite gaps and are needed revamp to give Artificial Intelligence Powered System. Such systems not only help to accomplish day to day compliance processes, rather help organizations with inbuilt intelligence in decision making and data analysis simultaneously. As more and more organizations are embarking on the journey of digitalization and facing COVID -19 like situations, and working on future workforce there is a heightened need for systems which are AI Powered systems. In my current blog I would like to share my thoughts on how artificial intelligence enabled systems can be useful to manage Product Safety Stewardship processes, Environmental Permit Management and Health and safety processes.
Visualize a scenario a Product Steward working on introduction of a new product to into the organization and gathering required raw material information and compiling the associated regulatory data. He needs to pain strikingly work on pulling all the data from the raw material and generate the component. Instead of manual task if a system can automatically identify the required information from the supplier data sheet and propose to product steward what is required information for approval. This system not only help in compiling the required information rather helps in different analytics for viewing the cross-sectional data of the raw material. Similar to the raw material information system can introduce different checks on the information to ensure that the raw material meets the company standards. If needed system can generate Labels automatically, it can help in rapid use within the organizations. Even such chemicals Standard Operating Procedures can be generated automatically using Natural Language Processing algorithms, which not only populate required chemical information rather can generate the operating instructions.
Once the raw material is created product Stewards will work on compiling the information and deriving dependent information. At times such information is not available at handy and company has a reference list of product information for which transport classification, GHS classification is carried out, system can work with decision algorithms to automatically identify the class of the chemical and necessary characteristics which can be of help. Product Stewards can analyze the proposed data and can either approve or can take to subsequent stages of further analysis to approve for use within the organization. When such data is compiled within the organizations AI systems can automatically generate the sectional data for each data based on GHS classification. There are already couple of GHS classification assessment utilities are available in open source platform, which can be evaluated for further use. Even some software companies offer such Machine Learning tools as a separate offering. Such systems can be used to analyze chemical control information, substances causing issues etc.
To visualize such scenario might seem difficult from a viewpoint of standard regulatory content, but once the systems are trained with sample data of information, they are very much capable of generating the information automatically. These types of systems can be used either as a proposal view to understand the data and necessary changes can be introduced to modify as needed. These processes can also be provided with necessary website scraping abilities which can navigate to different websites to pull the information like Safety Data sheet or even regulatory information like from ECHA Websites. These systems can be designed to automatically pull information from various manufacturers sites using different APIs. For example, for identifying product chemical compliance status the automation tool along with AI system can directly access the SDS contents of the manufacturers and provide the relevant information. Those can be peer reviewed for approvals and loading into the systems. These information when linked with Chatbot capabilities can answer to users questions within the organization. Like uses, misuses of chemicals and other information as needed for Hazcom members.
Other type of artificial intelligence driven software systems is for Environmental permit management. Such systems when used to not only capture the environmental parameter information but also help in prediction of emission levels based on future status of equipment or plant operation. Such algorithms can also be designed to do automatic speciate the pollution parameters to identify the source which is causing the issue. These types of systems will not only help in managing the operational compliance but also ensuring necessary adjustments are made to systems to ensure continued compliance. Such analytics can also be introduced to domains like Water Discharge Management, ETP operations management etc. to understand even the functioning of the Effluent Treatment plant or even Water Treatment plant. AI can also be built into CEMS data assessment and can automatically generate exceptions suggestion and possible root cause and even maintenance notifications.
Other type of AI Powered systems is around Health and safety management. Which are to manage the personal health management as well as risk management. Intelligence can be introduced for automatic analysis of health monitoring data via sampling sensors to suggest various personal analytics like safety of the person operating in such environments and suggestion of substitution person who can be fit to perform in such conditions given his health conditions. System can also be designed to use AI to generate Qualitative risk characteristics of the chemicals based on the vendor safety data sheet, which can further be used for risk assessment systems. In my previous blogs I have already highlighted how AI can be used to automatically log an incident, identify the equipment allocation or availability, PPE Violations or even Risk assessment.
These systems also be coupled with Social Site links to provide the real time status of the product perception and manufacturing operational status by various customers or users around the world. Different sentiment for product its positivity or negativity can be checked to decide on necessary controls to manage the acceptance or seeking alternatives. The use of advanced analytics using machine learning algorithms can provide cross sectional view of the data for decision making.
The use of AI, Big Data, IoT and Block Chain enabled EHS systems can not only change the way we are working with systems, rather they truly transform systems in the current digital age and provide delighted end user experience. Though technical details of each process explained above can be done in separate blogs in coming days, given the current scenario of COVID-19, scenario software companies can assess how best they can use their existing functionalities as core and extend the capabilities by digital technologies to redesign their systems which are not only future proof but are aligned with the digital dexterity of future employees.
To conclude, companies already working on future work force based on digital technologies and when software’s are also redesigned to meet to future workplace that is where the true business value would be. It needs careful separation of Transactional work with AI capabilities as a modular approach so as to achieve wider acceptance. Not only redesigning the modules even it needs some early partners to co-innovate environment to develop future system which provide resilience. Some of my earlier blog posts can be checked for details on each topic. In my upcoming blogs I would like to share my thoughts on each sub area in a detailed manner, how intended functionalities should be !.