Updates
News and Regulatory Updates
FDA and USDA recalls, DSCSA updates and state laws that affect packaging lines, each with a link to the official notice.
See the updates →Guides and tools for the plant floor.
How machine vision works, how to light a fault, two free tools to check the numbers yourself, and articles on specific inspection jobs.
Resources
What guides and tools does JM Automated Solutions publish?
Guide
How machine vision works
The camera, light, lens, and software that check product on a line, and how each picture becomes a pass or a reject.
Read the guide →Guide
Lighting and optics for inspection
How the angle, spread, and color of the light decide what a camera can see, and which lens keeps a measurement steady.
Read the guide →Guide
How much does a label inspection system cost?
What drives the price of a label inspection system, the cost tiers, and how each station is quoted.
Read the guide →Tool
Imaging calculator
Estimate the focal length, the angle of view, and the size of one pixel on the part.
Open the calculator →Tool
Barcodes
Work out the GS1 check digit, then draw the barcode.
Open the barcode tools →Articles
Specific inspection jobs, start to finish.
Long-form articles by Jorge Enrique Flores Montano on how JM Automated Solutions approaches specific inspection jobs, with the method, the numbers and the sources.
Article
Adding DSCSA serial numbers to pre-printed pharma labels
Print the serial inline or buy it printed, then check every label: barcode grade, missing ink, lot and expiry text, and the serial records.
Read the article →Article
How vision inspection catches double seam defects
Five cameras, a dark-field light and seam height on every can, and how a run of rejects tells maintenance the seamer is drifting.
Read the article →Article
Reading variety codes on unlabeled cans
A GigE Vision camera, a dome light and deep learning OCR read the three-letter code on every unlabeled can before it reaches the labeler.
Read the article →Article
Label verification at the labeler exit
A smart camera at the labeler exit confirms every label landed flat and its code matches the live production order.
Read the article →Article
Fill level inspection in clear, amber and opaque bottles
Near-IR backlight for clear PET and amber, SWIR for opaque HDPE, and a fill tolerance set on the HMI.
Read the article →Article
Deep learning OCR for packaging codes
Why deep learning OCR, which needs no per-code training, is the standard read layer on every JM Automated Solutions system.
Read the article →Article
The JM Automated Solutions vision HMI
Live image, pass/fail, false-reject counts and recipe changeover: the one operator screen behind every JM system.
Read the article →Published research
What research has Jorge Enrique Flores Montano published?
Research by Jorge Enrique Flores Montano on adaptive AI architecture, industrial control authentication and cryptographic entropy, published as preprints on Zenodo. Preprints are not peer-reviewed, and these articles describe research directions, not test results from a JM station.
Preprint
Independence as an Architectural Property
A research direction for multi-source cryptographic entropy: why entropy architectures should design for verifiable independence between their sources rather than assume it.
Read on Zenodo →Preprint
Latency-Aware Authentication in Industrial Control Environments
Consequence-graded authorization for control systems where decisions happen in milliseconds, beyond the latency budget of web authentication.
Read on Zenodo →Preprint
Supervisory Primacy
Human-in-the-loop AI orchestration for high-consequence domains: how human authority can be built into an adaptive AI system as an architectural property.
Read on Zenodo →Preprint
Eight Structural Principles for Adaptive AI Architecture
From physical law and cybernetics to engineering constraints on viable adaptive systems.
Read on Zenodo →Preprint
Adaptive Resilience
Why AI systems must remain viable in any future, and what that means for how adaptive systems are designed.
Read on Zenodo →