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LCP Optimiser included in IBM’s SAFE Framework

The LCP Optimiser, a software application developed by Genix for its asset management joint venture Softchill Pty Ltd, has become one of the first Australian applications to be included in IBM’s Solution Architecture for Energy and Utilities Framework (SAFE) which is designed to enable utilities to extract value from information by leveraging existing data sources in an integrated manner.

The LCP (Life Cycle Plan) Optimiser has been developed to facilitate the optimisation of capital and maintenance expenditure in large fossil & nuclear power plants and other asset intensive industries. The LCP provides quarterly views of expenditure over a 40 year period and allows maintenance managers to develop scenarios based on actual experience, functional equipment grouping, project risk ranking (using the IS 31000 framework) and budgetary constraints to optimise maintenance schedules and expenditure.

The LCP draws on financial data from ERP systems and EAM and CMMS systems to generate its projections and facilitates feedback of proposed projects into enterprise platforms once these have been agreed. It also has the ability to streamline capital allocation decision-making at a fleet and portfolio level and has been used effectively to support investment and divestment decisions in the energy sector.

The application has undergone tests at the IBM Innovation Centre in Sydney and has been validated for use in conjunction with Maximo, the IBM CMMS (computerised maintenance management system) and on IBM middleware.

The LCP can be deployed in customer environments or used as part of a managed service and has the potential to deliver significant cost benefits to asset managers who have exhausted the savings potential inherent in improving asset management processes and CMMS implementations.

Commenting on the successful validation, Softchill Director, Charles Harvey said “The SAFE Validation is an important first step for the LCP as it provides the baseline for the enhancements to come. These will include the use of improved, algorithm-based optimisation techniques and integration with models that monitor and predict the health status of an asset.”