Getting your leak test right starts with data
This e-book explores the art and science of achieving a more reliable, accurate and faster leak test. We cover seven practical steps, ranging from getting station setup right, to how to effectively use data and digital process signature analysis.
5 tips to improve production line efficiency in 2022
Is machine vision data part of your IIoT strategy? It should be.
Machine vision images and related data can be used for much more than basic pass/fail determination during the process cycle. We get into how this data can be collected, correlated and analyzed will all other production data as part of a comprehensive IIoT strategy.
events
ON-DEMAND: Quality Digest Live Presents: Process Signature Analysis
Better Tools for Data Analysis Measurement/Visualization are Improving Yield and Reducing Warranty Claims
Sciemetric CEO Nathan Sheaff talks to the editors of OEM Off-Highway Magazine about how “Industry 4.0” is really about breaking down data silos and making effective use of production data to increase yield, improve quality and optimize processes.
You need to go deeper than MES
Mathew Daniel, Sciemetric’s VP of Operations, is featured in Manufacturing Technology Insights Magazine where he discusses how manufacturers must go deeper than conventional manufacturing execution systems (MES) to achieve the quality and efficiency benchmarks demanded by Industry 4.0. This is about taking data collection and analysis to a new level with what Frost and Sullivan calls Manufacturing Performance and Quality Management (MP&QM).
Temperature Effects on Reported Leak Rate
Sciemetric product launch manager Robert Ouellette shares with Quality Magazine how quality engineers can measure and compensate for the sometimes dramatic effects of temperature variations on the accuracy and repeatability of a leak test.
Quality: Starting with Effective Data Management
Richard Brine, Sciemetric’s CTO, discusses with Industrial Machinery Digest how manufacturers must evolve beyond scalar data collection and analysis alone to rise to the big data challenge posed by Industry 4.0. He outlines the need for centralized collection and analysis of the digital process signatures, or waveforms, generated by every cycle of the process and test stations on the line.
Data holds the key to refining processes
In the pages of Industrial Technology Magazine, Sciemetric CEO Nathan Sheaff highlights five things manufacturers can easily do with their process data right now to take the guesswork out of limit setting, optimize test cycle times, trace the root cause of defects, predict maintenance requirements, and launch machines and lines faster.
Harvesting data for Industry 4.0 profitability
Derek Kuhn, Sciemetric’s senior vice-president, takes to the pages of APMA Lead, Reach, Connect to explain why auto manufacturers must look beyond data related to the performance of machines and business processes if they wish to succeed in a sector that is rapidly being redefined by Industry 4.0 and Manufacturing 4.0 principles. They must also collect, serialize and analyze the reams of production data generated by the process and test stations on the line.