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MOM 360™ - Composable Enterprise MES/MOM

Видавець: Symphony Industrial AI

Agile MES deployment and optimizations for actionable insights in real time

SymphonyAI Industrial channels the power of rapidly evolving IIOT, Artificial Intelligence, and big data technologies to deliver industrial insight that provides exponential value to our customers.

Traditional MES/MOM can be characterized as significant cost and long implementations with little flexibility to adapt. MOM 360™ is built on a composable, workflow-driven application architecture which enables organizations to turn on and implement only the operational processes that are required, thus reducing the time-to-value.

Functions provided by MOM 360™ include:

· Materials verification

· Recipe management

· Smart changeover

· Production scheduling

· Quality

· CAPA

· Traceability

· Sustainability

· Shipping and receiving

· Inventory execution

· Lab data management

· Incident management

· OEE

· Capacity and througput

SymphonyAI Industrial solutions serve a broad range of industries from process to discrete to naval and marine.

MOM 360™ is unique in that it provides:

· Low-Code Library – Pre-built library of thousands of processes (shipping/receiving, quality execution), hundreds of connectors (ERP, PLC, Sensors), and MOM applications

· Composable MOM – Low code, drag & drop visual workflow-based application composer; enables rapid deployment with pre-built MES & Plant Operations applications, as well as configuring/deploying new solutions using our low-code library to your site’s specific needs

· Enterprise MOM – Enterprise Management capability empowers operations management to rapidly deploy applications across your fleet of plants – leveraging our Enterprise Application Library providing governance and speed; Enterprise Manufacturing Operations Insights enable benchmarking to drive best in class operational productivity

· AI Continuous Improvement – Multivariate analysis to optimize production processes, maintaining the “golden batch” with near real-time set point advisories

Огляд

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