Going Electronic Without Losing Control: eDHR Done Right
Going electronic in a regulatory world – do I take the plunge? It’s a common dilemma that manufacturers who must comply with stringent medical regulations will always have.
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The Real Reasons Manufacturers Are Always Replanning
Ask any production planner how often their schedule survives a full week untouched, and you’ll get a knowing laugh. In discrete and process manufacturing, replanning isn’t the exception. It’s the rhythm of the job. The question worth asking isn’t how do we stop replanning. It’s why does it keep happening, and is our planning stack actually built to handle it? Where APS Fits, and Why It’s Not ERP …
Latest News: How One Leading Manufacturer Deepened Its Eyelit Technologies Partnership
MACOM Technology Solutions has expanded its use of Eyelit’s Manufacturing Operations Management (MOM) / Manufacturing Execution System (MES) platform, deepening a partnership built on smarter, more connected manufacturing. As a leader in optimized planning, scheduling, and execution systems for manufacturers, Eyelit continues to help companies like MACOM drive greater visibility, efficiency, and control across their …
Matching the Right AI to the Right Manufacturing Problem
One of the most common pitfalls in manufacturing AI adoption is treating AI as a single, uniform technology. Organizations invest in a platform or a model, apply it broadly, and then are surprised when results are inconsistent, strong in some areas, underwhelming in others. The underlying reason is usually a mismatch between the type of …
Eyelit Technologies Version 10.1 Innovates Manufacturing Operations Management (MOM) Through Agent EyeQ
Key advancements include Agentic AI, prescriptive inference, transparent forecasting, and end-user configurability Holmdel, NJ — July 2026 — Eyelit Technologies (Eyelit), a leader in optimized planning, scheduling, and execution systems for manufacturers, today announced the release of Eyelit Version 10.1 which highlights Agentic AI, Demand Planning and advancements across the fully integrated manufacturing operations management (MOM) applications suite. Built for discrete manufacturers …
Eyelit Technologies Version 10.1 Release Notes
Version 10.1 is the most significant release in Eyelit’s history bringing agentic AI, a reimagined demand planning platform, deeper execution intelligence, and hundreds of enhancements across MES, APS, and supply chain planning. Here is what’s new. Demand Planning Version 10.1 is a ground-up rearchitecting of demand planning for the AI era. The capabilities below represent …
Closing the Gap Between Planning and Execution in Manufacturing
In manufacturing, execution rarely aligns perfectly with the original plan. A machine goes into an unplanned maintenance state. A supplier delivers late. A quality hold pulls a batch off the line. An urgent customer order changes the demand picture mid-shift. Within hours of a production day starting, the schedule that looked optimal at the beginning …
Why Purpose-Built Software Still Matters in an AI-First World
There is a growing assumption in software that AI-assisted development is rapidly closing the gap between general-purpose tools and specialized applications. If a capable model can generate code quickly and iterate on it in real time, the argument goes, purpose-built software becomes less necessary. Domain expertise gets absorbed into the model, and the barriers to …
SLMs vs. LLMs: The Edge Advantage for Factory Operations
As manufacturers evaluate AI strategies, one of the most important architectural decisions is where AI inference should run and what type of model is best suited for shop floor operations. For many complex manufacturing environments, Small Language Models (SLMs) deployed at the edge offer meaningful advantages over large language models running in the cloud. Understanding those advantages …
Why General-Purpose LLMs Fall Short in Complex Manufacturing
There is a lot of discussion right now about the role of large language models (LLMs) in manufacturing. The excitement is understandable. LLMs like those powering ChatGPT or Gemini can reason through complex, multi-step problems, generate code, summarize documents, and respond to natural language queries across a wide range of topics. For many business functions, …
