How Neural Manufacturing Can Drive Innovation In The US Chemical Industry

May 27, 2021

The past decade of the economy is characterized by the increasing integration of informational and computational technology into traditional industrial and manufacturing sectors. Strengthened by the rapid development of computing power and driven by increasing demands for production, these Industry 4.0 strategies, as they have been dubbed, have had a huge impact on chemical supply companies as well. Now, more than ever, the COVID-19 pandemic has forced chemical companies to reassess their daily operations and broader organizational designs regarding manufacturing.

Like most other sectors, the chemical sector witnessed intense turbulence and disruption in its operations due to the pandemic. From the breakage in global supply chains and sudden shifts in demand to the volatility in prices across the spectrum, the industry has seen a transformation in the nature of how businesses operate. The emphasis on sustainability and the need for resilient supply chains have never been higher. 

What is Neural Manufacturing?

Neural manufacturing is a set of techniques that seek to optimize how businesses approach manufacturing. In neural manufacturing, each unit or point within a supply chain acts as a “node.” Each of these nodes continuously receives, processes, and transmits data to meet an end goal through advanced technologies such as machine learning, cloud technology, blockchains, AI, and IoT. This enables the proper availability of operational information across the ecosystem, allowing partners in an ecosystem to collaborate and work together to achieve optimum performance. The neural manufacturing approach transforms the fundamental nature of manufacturing from a traditional hub-and-spoke framework to an intelligent distributed system where the central, physical factory plays a smaller role in a larger, information-rich ecosystem. 

Benefits of Neural Manufacturing

Essentially, this approach allows the units to have a holistic situational awareness of the supply chain. Operational information about all units from feedstock to the finished goods is strategically disseminated throughout the system, making it ideal for businesses to be well-informed about other nodes' varied and ever-changing requirements. These nodes then adapt accordingly, enhancing the productivity and resilience of the entire manufacturing and distribution processes. The autonomous connectedness made possible by the approach facilitates real-time goal-setting and elimination of bottlenecks, thus bringing an unmatched degree of responsiveness and efficiency to the system.

For chemical distributors, the timeliness of shipments is an essential requirement. For specific niche segments, like bioactive compounds and vaccine raw materials, bottlenecks in the supply chain will prove to be disastrous. Neural manufacturing can be used to identify root causes of delayed shipments and establish end-to-end supply-chain visibility. The neural network model also enables an entirely responsive and automated process that leaves room for flexibility to respond to situational contingencies. The model also facilitates enhanced safety measures for chemical and process manufacturers in this new post-pandemic age of social distancing and work-from-homes.

The businesses in the chemical industry must reassess their approach to manufacturing to ensure a rapid rebound from the COVID-19 pandemic and retain a competitive edge by establishing a responsive, optimum, and resilient framework to deal with potential future shocks. Neural manufacturing is a very lucrative candidate to replace the traditional factory-based supply chains riddled with unseen inefficiencies.

Latest Blogs

NEVADA

SEATTLE

TEXAS

OHIO

IDAHO

MONTANA

CHICAGO

HAWAII

GEORGIA

NEW YORK

NEW JERSEY

BOSTON

CALIFORNIA

ARIZONA

FLORIDA

MICHIGAN

PENNSYLVANIA

ALASKA

ILLINOIS

COLORADO

WASHINGTON

CAROLINA

VIRGINIA

INDIANA

MINNESOTA

OREGON

MASSACHUSETTS

WISCONSIN

TENNESSEE

ALABAMA

MISSOURI

LOUISIANA

IOWA

UTAH

CONNECTICUT

MAINE

KENTUCKY

KANSAS

WYOMING

ARKANSAS

MORE..