Abstract: Embodiments of the invention are generally directed to a system and method for service parts planning in a network having one or more service parts. For at least a subset of the one or more service parts, a calculation is performed to determine a location within the network at which allocating the service part provides the greatest gain in system availability per item cost. In an embodiment, the calculations are based, at least in part on machine-specific information. In one embodiment, inventory position is determined based, at least in part, on a unique identifier associated with a service part.

Abstract: Embodiments of the invention are generally directed to a system and method for service parts planning in a network having one or more service parts. For at least a subset of the one or more service parts, a calculation is performed to determine a location within the network at which allocating the service part provides the greatest gain in system availability per item cost. In an embodiment, the calculations are based, at least in part on machine-specific information. In one embodiment, inventory position is determined based, at least in part, on a unique identifier associated with a service part.

Abstract: Embodiments include a system for forecasting demand data for new products. The system and method may include generating a phase-in group profile based on similar products. The phase-in group profile may have multiple demand profiles for low, medium and high demand variations. These demand profiles may be applied to new products in the same phase-in group to generate a forecast profile.

Abstract: Embodiments of the invention are generally directed to a system and method for service parts planning in a multi-echelon network having one or more service parts. For at least a subset of the one or more service parts, a calculation is performed to determine a location within the multi-echelon network at which allocating the service part provides the greatest gain in system availability per item cost. In one embodiment, the calculations take into consideration violations of incremental optimal allocation. In an embodiment, the calculations take into consideration violations of convexity.

Abstract: Profit optimization methods and systems for a supply chain are described. An implementation of the technique includes determining the initial cost of components required to manufacture a product, dynamically determining the cost for substitution of at least one product component, dynamically determining the location of at least one substitute component, and manufacturing the product for the lowest cost based on the results of the cost of substitution and substitute component location determinations. At least one of the cost of substitute components and the component locations may be determined at or near the time of manufacture.

Abstract: Embodiments of the invention are generally directed to a system and method for service parts planning in a multi-echelon network having one or more service parts. For at least a subset of the one or more service parts, a calculation is performed to determine a location within the multi-echelon network at which allocating the service part provides the greatest gain in system availability per item cost. In one embodiment, the calculations take into consideration violations of incremental optimal allocation. In an embodiment, the calculations take into consideration violations of convexity.

Abstract: Embodiments of the invention are generally directed to a system and method for service parts planning in a multi-echelon network having one or more service parts. For at least a subset of the one or more service parts, a calculation is performed to determine a location within the multi-echelon network at which allocating the service part provides the greatest gain in system availability per item cost. In one embodiment, the calculations take into consideration violations of incremental optimal allocation. In an embodiment, the calculations take into consideration violations of convexity.

Abstract: A system and method for generating or adjusting a demand forecast for a phased-out product is described. A demand forecast may be generated based on the historical data for the phased-out product and trends found in similar products that have been phased-out.

Abstract: A system and method for generating or adjusting a demand forecast for a phased-out product is described. A demand forecast may be generated based on the historical data for the phased-out product and trends found in similar products that have been phased-out.

Abstract: A system and method for generating or adjusting a demand forecast for a phased-out product is described. A demand forecast may be generated based on the historical data for the phased-out product and trends found in similar products that have been phased-out.

Abstract: Systems and methods consistent with the present invention are provided for selecting a set of models, each of the set of models providing a forecast representative of a demand for a product. In one embodiment, a method includes receiving data representative of a past demand for the product; determining, in a sequence, whether the received data corresponds to at least one of one or more known demand patterns; and selecting the set of models based on the determined demand pattern, such that at least one of the models provides the forecast representative of the demand.