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.
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.
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 …
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 …
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 …
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 …
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 …
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 …
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, …
For anyone who has managed a production floor, you’ll know that one of the lynchpins of the operation is your team leaders and supervisors. These are your eyes and ears around the shopfloor. They know how to make things run smoothly, they know what tends to cause problems, and they’ve typically built-up years of experience across a range of areas. As people operating directly in that environment, they are uniquely placed to manage daily operations and deliver results. The question is: how do you leverage this valuable resource even more?
What is Inventory Days on Hand (DOH) “Inventory Days on Hand is a calculation of how many days inventory will last given the current rate of sales.” (Key Accounting Principles Volume 1 by Neville Joffe) DOH Formula 1 Inventory Days on Hand = Average Inventory / Cost of Goods Sold x 365 DOH is the …