We all appreciate and understand the role of the NDT department, which is to maintain the quality and integrity of materials and components to ensure safety and continued operation. NDT departments and personnel around the global do this with aplomb. However, their importance is sometimes overlooked and their success only evident with thought. Perhaps NDT is the only department where the overall success can be measured in lack of catastrophe?
This hard working, inconspicuous, department is about to take centre stage. Quietly they have been going about their work testing components and collecting data, and it is this data that is about to burst on to the scene. This data holds the key to the reduction of waste and improved productivity; it is the kernel that manufacturing data should be built around.
To improve quality, we must drive change, otherwise how can we expect the quality of a product to improve? The quote often attributed to Einstein comes to mind: “the definition of insanity is doing the same thing over and over again, but expecting different results.” The data produced by the NDT department is the key to this. To decide what to improve we must understand when and why a problem arose.
In the best manufacturing environments, we see people trying to do this but lacking the tools. JetSoft often hears informal discourse between production and the NDT department. A simple example would be:
NDT: “Defect X is appears to have recently become more common.”
Production: “in your experience why do you think this might be happening?”
NDT: “It seems to be more apparent on product W in batches Y and Z.”
Production: “We changed the supplier of a raw material recently that went into those batches.”
NDT: “That seems a likely cause, lets investigate that further.”
But even when this does happen it is insufficient, because it relies on the NDT personnel spotting a rise in the occurrence of a defect and which product and batches that trend affected. It also relies on the production manager knowing about a supplier change. Even if this is spotted and the assumptions are correct there is a delay in information exchange and possible correction. Manufacturers have all the data required to automate this process, but lack the tools
This is where JetSoft can help. Our OverSeer solution is structured around building a central database repository for NDT information. Once installed it is easy to navigate your data, monitor trends, gather insight, create reports, set-up notifications and alerts and expose the data to other production processes and systems.
JetSoft works collaboratively to ensure that our solution fits your individual and specific circumstances, so please get in touch to discuss how we may be able to help you.
This hard working, inconspicuous, department is about to take centre stage. Quietly they have been going about their work testing components and collecting data, and it is this data that is about to burst on to the scene. This data holds the key to the reduction of waste and improved productivity; it is the kernel that manufacturing data should be built around.
To improve quality, we must drive change, otherwise how can we expect the quality of a product to improve? The quote often attributed to Einstein comes to mind: “the definition of insanity is doing the same thing over and over again, but expecting different results.” The data produced by the NDT department is the key to this. To decide what to improve we must understand when and why a problem arose.
In the best manufacturing environments, we see people trying to do this but lacking the tools. JetSoft often hears informal discourse between production and the NDT department. A simple example would be:
NDT: “Defect X is appears to have recently become more common.”
Production: “in your experience why do you think this might be happening?”
NDT: “It seems to be more apparent on product W in batches Y and Z.”
Production: “We changed the supplier of a raw material recently that went into those batches.”
NDT: “That seems a likely cause, lets investigate that further.”
But even when this does happen it is insufficient, because it relies on the NDT personnel spotting a rise in the occurrence of a defect and which product and batches that trend affected. It also relies on the production manager knowing about a supplier change. Even if this is spotted and the assumptions are correct there is a delay in information exchange and possible correction. Manufacturers have all the data required to automate this process, but lack the tools
This is where JetSoft can help. Our OverSeer solution is structured around building a central database repository for NDT information. Once installed it is easy to navigate your data, monitor trends, gather insight, create reports, set-up notifications and alerts and expose the data to other production processes and systems.
JetSoft works collaboratively to ensure that our solution fits your individual and specific circumstances, so please get in touch to discuss how we may be able to help you.
