Mathematics lies at the heart of all our analysis. Our mathematical services cover mathematical modelling, simulation, analytics, and visualisation, as relevant for a particular artificial intelligence application.
Mathematical and numerical techniques applied by us have included:-
Data science is the extraction of knowledge from data, and analytics is the discovery and communication of meaningful patterns in data. We work in partnership with clients for analytics and data derived solutions.
We integrate the engineering, financial, and management processes with the purpose of performing following analysis:-
Analysis is performed on all types of data all types of life data, including complete, right censored (suspended), left censored, interval censored and free-form data, entered individually or in groups. The distribution model appropriate for a given data set is selected after performing several types of goodness-of-fit tests in order to rank the available distributions.
We perform Life Data Analysis to study and model the observed product lives.
Life data can be lifetimes of products in the marketplace, such as the time the product operated successfully or the time the product operated before it failed.These lifetimes can be measured in hours, miles, cycles-to-failure, stress cycles or any other metric with which the life or exposure of a product can be measured. cycles-to-failure, stress cycles or any other metric with which the life or exposure of a product can be measured.All such data of product lifetimes can be encompassed in the term life data or, more specifically, product life data. The subsequent analysis and prediction are
described a life data analysis.
The degradation analysis is performed by extrapolating the expected failure times of a product based on measurements that reflect how some performance measure (e.g., increase in crack propagation, decrease in tread depth, increase in vibration, etc.) has degraded for sample units over a period of time. The choice of the Linear, Exponential, Power, Logarithmic, Gompertz or LloydLipow models is an option to analyse thedegradation data, and generates Degradation vs. Time plots on either a linear or logarithmic scale.
The warranty analysis converts warranty claims data (sales and returns) that are readily available in many organizations into failure/suspension data sets that can be analysed with traditional life data analysis methods. This analysis can be used to better understand the failure behaviour of products in the field and to generate forecasts of future returns that will be covered under warranty. The analysis can be performed from a choice of data entry formats to fit your particular needs: Nevada Chart, Times-to-Failure, Dates of Failure or Usage
We capture system failure and repair data in an event log format like those commonly used in the machine tools and other industries. If you have a log that records the date/time when a system downing event occurred and the date/time when the system was restored to operation, we convert this information to time-to-failure and time-to-repair data that can be analysed with life data analysis techniques. Some useful options in this folio include the ability to:
Specify which component/assembly is responsible for each event, and then perform the analysis for any level of the system configuration.
The ability to calculate the optimum replacement time provides a powerful opportunity to reduce a system’s maintenance costs while maximising uptime. We create an optimal Maintenance Planning that is generated based on cost vs. time plot designed to help you determine the most cost-effective time to replace a system’s worn or failed components.
