PrimeNumerics since its inception has been developing the Statistical Data Models.

Our Statistical Data Model Library provides the most comprehensive array of data analysis, data management, data visualization, and data mining solutions. Techniques include the widest selection of predictive modeling, clustering, classification, and exploratory techniques in one platform.

This is tried and true analytics platform which delivers successful business results for our customers.

Good data and sophisticated analysis only get you so far. For your best decisions, you must be empowered to interpret and act upon your data trends in a manner relevant to your business goals, customized for your company, in your industry, in your town, with your government policies and your business rules.

Our Statistical Data Model Library is easy-to-use analytic solution, incorporates the innovative Rules Builder that enables you to apply both business rules and analytic models to your business processes. Forecast, plan, and anticipate quality issues like never before. You can provide scoring solutions, meet supplier demand, and develop strategic options with unmatched business relevance, all with defined user roles and accompanying privileges company-wide.

Model	Business Situation	Basic Techniques
PN-001	Automotive Car Warranty claims Prediction.	Non homogeneous poisson process
PN-002	Analysis of an accelerated life test for electrical motor insulation.The purpose of the test is to estimate the median life of the insulation at the design operating temperature .It is the process of testing a product by subjecting it to conditions (stress, strain, temperatures etc.) in excess of its normal service parameters in an effort to uncover faults and potential modes of failure in a short amount of time.By analyzing the product's response to such tests, we can make prediction about the service life and maintenance intervals of a product.	Accelerated life model
PN-003	Analysis of failure of mica capacitor from circuit bords and predicted number of capacitors failing .	Binomial Model
PN-004	Analyze of recurrence data when the recurrence ages are grouped into intervals,instead of being exact ages and predict the mean function cumulative of time. Mean Cumulative Function (MCF) provides a valid statistical inference on recurrent adverse .	Mean Cumulative Function
PN-005	Analysis of the lifetimes of locomotive engine fans and predict the lifetime of engine fans	Bayesial method
PN-006	Analysis of Survival Time of Semiconductor in Two Batches.	Bayesial Analysis
PN-007	Analyze of recurrence data on repairs and mean cumulative function for the number or cost of repairs for a population of repairable systems.	Mean Cumulative Function
PN-008	Analysis of right censored data from a single population and predict the lifetimes of diesel engine fans	Weibull model
PN-009	Analyzed failure data for the dielectric insulation of generator armature bars(analyze two combined Failure Modes)	Reliability method
PN-010	Analyze the failure of bearing and predict the life of failure	Weibull Regression Model
PN-011	Analyze the number of cycles to fatigue failure of specimens of a certain alloy	Three parameter weibull analysis
PN-012	Analysis of component reliability and predict the number of components removed for maintenance.	Generalised additive model
PN-013	Forecast the automotive sales.	ARIMA model
PN-014	Analyze the data represent failure times of machine parts, some of which are manufactured by manufacturer A and some by manufacturer B. predict the lifetime ( which gives information of quality).	generalized linear model
PN-015	Analysis of recurrence data from repairable systems. Repair data analysis differs from life data analysis, where units fail only once. As a repairable system ages,it accumulates repairs and costs of repairs. cost of repairs for a population of repairable systems	Mean Cumulative Function (MCF)
PN-016	Analyze the capacitor failure and quality of capacitor.During the manufacture of a metal-oxide semiconductor (MOS) capacitor, causes of failures were recorded before and after a tube in the diffusion furnace was cleaned.	Pareto Analysis
PN-017	Method to model insurance claims data	Markov Chain Monte Carlo
PN-018	Analysis of Pump failure data . The number of failures and the time of operation are recorded for pumps. Each of the pumps is classified into one of two groups corresponding to either continuous or intermittent operation	Markov Chain Monte Carlo
PN-019	Analyzing Recurring Failures.Replacement of components such as Good as New or Bad as Old?	Non Pomogeneous Poisson Process
PN-020	Analysis of pump failure	Poisson and Nomal Model
PN-021	Comparing the repair performance of two systems.evaluate whether the population repaire(or cost) rate increasing or decreasing with age estimate average number or cost of repair per unist on warranty or over design life of the product,comparaing two or more sets of data from different disigns production peroids ,maintanance policies enviroment operating condintions etc. predict turure number and cost of repairs .	Mean Cumulative Function
PN-022	Predicts total maintenance cost ($) for next six months using time series method. This prediction will help planner (manager) to allocate the maintenance budget for next six month.	Forecasting Total Maintenance Cost
PN-023	Pareto analysis is used to identify critical problem by number of failures or by maintenance cost or by repair time.	Pareto Analysis
PN-024	Moving range chart is tests for special causes to make an individual measurements chart more sensitive to special causes of variation.	Moving Range Chart
PN-025	The accelerated life test of an insulating fluid and are the times to electrical breakdown of the fluid under different high voltage levels	Weibull Analysis
PN-026	This method to model insurance claims data of automotive car	Bayesial Analysis
PN-027	The number of failures of pumps and the time of operation are recorded of pumps. Predict the failure of pump.	Nonlinear Poisson Regression Random Effects Model
PN-028	Analysis of Microprocessor Failure data	Cox proportional hazards model
PN-029	Analysis of failure of Motor of scooter with operating temperature as a covariate	Cox proportional hazards model
PN-030	Analysis of Gas Turbine failure data	Reliabilty method
PN-031	Analyzed data from an accelerated test on the lifetimes of Air gap capacitors as a function of operating voltage and temperature. It is the process of testing a product by subjecting it to conditions i.e. temperatures, voltage in excess of its normal service parameters in an effort to uncover faults and potential modes of failure in a short amount of time	Weibill Analysis
PN-032	Monitor the number of defects per motor.The motor of the same model are inspected, and the number of defects per motor is recorded.	C-CHART
PN-033	Monitor the number of failing circuits from the circuit manufacturing process.	np-Chart
PN-034	Analyzed data from a strain-controlled fatigue test on specimens of a type of superalloy.	Weibull Regression Model
PN-035	Monitor number of failing circuits produced by the circuit manufacturing process.	p-Chart
PN-036	Estimating cost of product in manufacturing	Simple Linear Regression
PN-037	Forecast Repaircost of Motor Failure .	Multiple Linear Regression Method
PN-038	Forecast the mean residual life of an asset	Mean Residual Life Function
PN-039	Analysis of failure cost by failure code for particular asset.	Cause and cost Chart
PN-040	Analysis of Risk Priority Number (RPN) data to evaluate risk level of component for perticular asset.	Failure Mode Efect Analysis
PN-041	Monitor the Total claim cost,Labor cost ,complaints of customers in warranty of cars	Tile Graph
PN-042	Forecast the Total Maintenance cost	Multiple Linear Regression
PN-043	Analysis of failure occurs in Wind Turbine	Pareto analysis
PN-044	Automotive car insurance claim prediction	Poisson regresssion
PN-045	Analysis of motor failure with different degradation stage	Weibull model
PN-046	Analysis of wind turbine failure data and identify critical problem by failure of bearings	Pareto Analysis
PN-047	Nurse scheduling Problem	Optimization
PN-048	Job shop scheduling Problem	Optimization
PN-049	Depot location problem	Optimization
PN-050	Predict the Probability of defualt	Logistic Regression
PN-051	Failure prediction	Similarity based modeling

Technologies

Clients