Manufacturing process management (MPM) and model-based manufacturing (MbM) bridge the gap between the virtual design realm and the physical product/process manufacturing realm as part of an organized software architecture. These technologies are not only applied within the four walls of a plant or a corporation's multiple manufacturing sites. They can be applied holistically, with workflow to manage multiple recipe variants and labeling change/requirements, and/or handle certificates of compliance (CoCs) and certificates of analysis (CoAs) from suppliers.
Gartner defines manufacturing execution systems (MES) as a specialist class of production-oriented software that manages, monitors and synchronizes the execution of real-time physical processes involved in transforming raw materials into intermediate and/or finished goods. These systems coordinate this execution of work orders with production scheduling and enterprise-level systems like ERP and product life cycle management (PLM). MES applications also provide feedback on process performance, and support component and material-level traceability, genealogy and integration with process history, where required.
Gartner defines operational technology (OT) as “hardware and software that detects or causes a change, through direct monitoring and/or control of industrial equipment, assets, processes and events”. OT security includes practices and technologies used to protect them, but these practices and technologies are now evolving into distinct categories to address the growing threats, security practices and vendor dynamics.
Supply Chain Simulation Software is designed to model, analyze, and optimize the operations of a supply chain virtually. It allows manufacturers, logistics providers, retailers and consultants to create a digital replica (or simulation) of their supply chain processes, including production, inventory, warehousing, distribution, and transportation. This software is also used to understand how a supply chain behaves under different conditions or scenarios without having to experiment in the real world. It also utilizes optimization algorithms to find the most efficient ways to allocate resources, schedule production, and manage logistics.This helps in reducing risk and asosciated costs, improves decision making leading to increased efficiency, which eventually enhances customer service.