AH Group of Companies’ Post

Reliability and Survival Analysis We’re interested in knowing the answers to the following questions: • What percentage of the motors is expected to fail between 60,000 hours and 70,000 hours? • What percentage of the motors will survive past 40,000 hours? • 18.6856% of the XXXs are expected to fail between 60,000 hours and 70,000 hours. • 92.2680% of XXXs are expected to survive past 40,000 hours. #reliabilityengineering #sixsigma #qualitysystem #improvement

#parenting #absolutes #engineering #suites #offers the #equilibrium #composition of #designideas and #precision #simulation #services, specializing in #redesigning your #manufacturingprocess and #processing #equipment. Engage in #production #enhancement and #maximizereturns and #profits through simulation-guided #analysis #manufacturing #units. #discovermore at https://lnkd.in/dJRusw-X

Simulation is the #key to #enhanced #process #plant #design and #optimization. #leverage #simulation - based #analysis to #streamline your #processplant #operations. Our #solutions #offer #precise #modelling of plant #behaviour, enabling you to predict #performance, #troubleshoot #issues, and implement #proactive #measures for enhanced #productivity. #request a #quotation at https://lnkd.in/d6EsuaCq

Machine malfunctioning isn’t just inconvenient—it can negatively impact part quality, too. In the weeks before machines visibly need repair, parts produced are prone to issues like chip build-up and subpar surface finishes. To combat this problem, Reata Engineering created a proactive maintenance program to keep machines in optimal operating condition. Here's how we stay ahead: https://bit.ly/45lkBoF #proactivemaintenance #manufacturing

🚀 Turning Breakdowns into Breakthroughs: 793D transmission failure taught me that every setback is a setup for a comeback. Failure analysis isn’t just about fixing the issue; it’s about making systems and processes stronger and more resilient. ⚙️#FailureAnalysis #Engineering

Repaired machines ✅ On-time production ✅ Go ahead, make those weekend plans 😎 #MachineHealth | #PredictiveMaintenance | #Manufacturing

This is the second post on how to measure the cycle time of a process. Again, the cycle time is the fastest repeatable time in which you can produce one part. Hence, as part of a series on manufacturing speed measurements I continue with more details on what cycle times really are. This is the second post on how to measure cycle times (post 1 here), with an additional third post focusing on the details of manual cycle times coming up next. #allaboutlean #operationalexcellence #leanmanufacturing #leansixsigma

Read Forbes Published full Blog here: https://lnkd.in/eSxMDeUf The harsh reality is that most tools and techniques used today to investigate organizational and programmatic failures, human performance deficiencies, equipment failures and accidents/incidents originated in the 20th century. For example, the “5 Whys” root cause analysis technique was developed in the 1930s for the automobile manufacturing industry. #rootcauseanalysis #problemsolving #bluedragonips

The normal distribution is found in nature just about everywhere from a theoretical and practical sense: height, test scores, reading ability, etc. Theorizing about cycle times in a manufacturing setting, you would expect to see the same thing, however this is not the case in practice. Many companies break down their processes into value-add time and required non-value-add time. Value-add time is, for example, the time it takes to screw in the bolt, or physically attaching two components together. Required non-value-add time would be the time it takes to get the parts and tools from their storage locations--still necessary for the assembly process, but more difficult to document in an absolute sense. Value-add time has been studied and is very well understood. For the most part, you cannot assemble faster than the sum of the value-add time because it does take time to perform any individual task. The required non-value-add time is more of a function of the assembly area set up, current condition, and the individual performing the assembly. Sometimes parts/tools are closer to the assembly location, assemblers move at different speeds, or some utilities are auto-retracting while other require the assembler to put them away. These nuances are often not fully accounted for when the required cycle time is calculated. As companies do their best to minimize required non-value-add work, the distribution of cycle times starts to form a shape that looks similar to a normal curve that is missing its tail in the front. By looking for this smashed normal curve in your data, you can start to see if the cycle time calculated for the task was a theoretical exercise or practical application. Remember, spontaneous combustion is feasible; spontaneous assembly is not! #manufacturing #industry4.0 #operations #mit