Life Cycle Engineering
LSC takes a system engineering approach to life cycle engineering. This includes Mechanical Engineering like CAD modeling, temperature prediction and structural analysis to estimate the operative loads, as well as Material Engineering to provide the damage accumulation under the operative loads.
Failure Analysis
LSC uses modern microscopy and analytical tools to conduct failure analysis of a wide range of engineering structures. A thorough failure investigation requires a careful and systematic approach where all possible evidence is collected, documented and analyzed. Evidence includes visual evidence covering a wide range of magnifications, such as can be obtained using a simple magnifying glass all the way up to scanning electron microscopes. Chemical analysis may be needed and special techniques such as experimental or analytical stress analysis and non-destructive inspection (NDI) may be needed. Quantitative NDI can be very useful in developing methods for managing situations where damage is known to be accumulating and leading to potentially catastrophic situations. Failure analysis, if correctly performed, can resolve any uncertainties about the validity of the original design, about the materials and manufacturing methods employed, and about the way the equipment has been used. If the basic design, materials, manufacturing or maintenance methods are found to be defective, then failure analysis provides a basis for sensible corrective action. This is a process often referred to as Retroactive Design.
Residual Life Analysis (RLA) Services
LSC uses modern analytical tools and material physics based damage modeling algorithms to conduct RLA of a wide range of engineering structures. LSC possesses highly specialized damage modeling algorithms for stress corrosion cracking (SCC), creep, low cycle fatigue (LCF) and thermal-mechanical fatigue (TMF) damage modes. LSC also provides high cycle fatigue (HCF) margin analysis services. Engineering applications where microstructual variability, inspection uncertainty and operational variability must be considered for RLA are also available