Manufacturers in the chemical industry are continuously facing challenges — recalls, inefficiencies, and quality issues to name a few — and those that do not adapt risk falling behind the competition.
Industry 4.0 technologies have already had a significant impact on manufacturing, including in the chemical industry, providing advanced solutions that enable manufacturers to operate with more agility.
One such technology, artificial intelligence (AI), is facilitating new levels of visibility and understanding of materials as they flow upstream, midstream and downstream across the supply chain. AI helps manufacturers work smarter and confront challenges head on, leading to optimized operations, and significant improvements in yield and safety.
Chemical manufacturers are becoming more and more aware of the power of data. Artificial intelligence used in manufacturing powers the contextualization of realtime data gathered in IoT systems, in order to deliver actionable insights that can improve the chemical manufacturing process.
Manufacturers can apply these actionable insights to significantly improve yield; AI is capable of monitoring multiple different production processes in realtime to spot areas for improvement. This has the potential to dramatically streamline operations, helping chemical manufacturers produce more in less time, using less materials and energy.
Some level of waste is typical in any given chemical manufacturing enterprise, be it from contamination, anomalies in recipe formulation, or overproduction. AI can help significantly reduce waste by supporting data-driven decision-making, in conjunction with predictions enabled through machine learning — a branch of AI that enables machines to learn from past behaviors to improve future actions, while refining accuracy over time. Underlying causes are identified, and corrective actions are suggested. Often times only a slight tweak to a chemical recipe can lead to a considerable waste reduction.
Temperature, stirring rate, pressure, rate of flow, process duration — these operational variables have a direct impact on chemical manufacturing outputs, and with AI, data captured in relation to these factors can be tracked over time, with any variations easily controlled and modified. Prescriptive analytics can optimize settings ahead of the manufacturing process, with adjustments made in realtime as required. Manual adjustments by human operators are susceptible to reactivity, inexperience, and error. But with AI making sense of realtime data, adjustments can be implemented before problems even occur, leading to consistency in production performance, and a predictable, improved yield.
As one of the world’s most strictly regulated industries, chemical manufacturing is subject to national and international protocols that oversee operational procedures such as production and distribution, as well as health and safety factors.
Chemical manufacturers can improve product and worker safety and increase regulation compliance with the help of AI working together with realtime data collection and advanced analytics.
Data captured by IIoT sensors can provide chemical manufacturers with information about the activities of personnel, and about chemical inputs and asset quality across the supply chain, providing key visibility — AI can then correlate data, identifying anomalies, leaks, environmental hazards, contaminants, defects, or employees working without the proper safety protocols in place.
Acting quickly is imperative to contain safety hazards within the chemical industry. AI can use data to alert manufacturers at the earliest stages of an event, promoting actions that contain the situation before it progresses out of hand. Moreover, machine learning can use information from the event to spot similar events more rapidly in the future, or ensure they don’t happen in the first place.
Clearly, artificial intelligence has tremendous potential for improving yield and safety in chemical manufacturing, enabling manufacturers to make the most of their data in order to optimize manufacturing operations.
Challenges may never cease to arise, but with an investment in AI, chemical manufacturers can ensure they have the tools to continuously rise above them.
AI-powered data insights drive manufacturing success in the chemical industry and beyond, improving not only yield and safety, but efficiency, quality, sustainability, and your enterprise’s bottom line.
ThinkIQ supplies Transformational Intelligence, taking manufacturing businesses through the 5 stages needed to reach fully automated Smart Manufacturing status.
Our technology goes far beyond analytics to reveal how every element of your supply and manufacturing chain may impact the final product.
ThinkIQ enables a material-centric view of operations using advanced AI and ML to correlate data, providing advanced visualizations of your manufacturing line (including supply chain), cause & effect identification, industry benchmark reporting, and cross-plant KPIs. Previously unseen correlations are revealed — even root issues — from your supply chain through the manufacturing process and outward to the end-user.
Previous technologies like ERP, MES, and MOM were generally passive. ThinkIQ’s Transformational Intelligence platform delivers actionable insights that transform manufacturing.
Experience the advantages of AI-powered contextualized data — Reach out to a ThinkIQ expert to get started, and to find out more about what a Smart Manufacturing transformation can do for your organization. Also, be sure to download our new eBook, “Using Computer Vision to Fill Manufacturing and Warehousing Blind Spots with Actionable Data” to learn how to gain greater visibility into your manufacturing process.