Abstract: Organizations/manufacturers have used scenarios to make business decisions. It has been difficult to apply scenarios in dealing with tactical opportunities due to lack of integration of changing inputs for consistent decision making. Conventionally, tools are cumbersome and depend on pre-structured and individually validated data requiring significant expert involvement. Present disclosure manages decision scenarios and optimizes total sourcing cost by obtaining various inputs and retrieving decision scenarios from a database. An optimization technique and/or a simulation technique is performed on the decision scenarios to obtain the total sourcing cost that is based on a quantity filled for each source-entity-destination combination and a corresponding unit lane cost. A decision scenario is selected from the pre-defined decision scenarios based on the total sourcing cost and an ordering schedule for associated demands is created accordingly.

Abstract: Present disclosure relates to method and synchronization system for synchronizing plurality of events associated with one or more processes in assembly line for tracing entity. Initially, information related to plurality of events associated with one or more processes from one or more devices is received, where each of the plurality of events comprises respective first timestamp. Upon receiving, the first timestamp between each of the plurality of events is synchronized by performing first level and second level synchronization. The synchronization converts first timestamp into second timestamp with respect to common reference timestamp. Further, the synchronization system may identify one or more defects based on quality value assigned to entity. Thus, the present disclosure helps the synchronization system to efficiently trace entity when a defect is identified and replaces/repairs the entity.

Abstract: State of the art approaches being used for material replenishment planning have the disadvantage that they fall short in addressing the realities of evolving demand mixes and product utilization. The technologies leverage inflexible statistical models which are tightly coupled to specific industries, business processes, and deeper assumptions and therefore the model and any optimization produce results where the quality of results is heavily curtailed as real business processes deviate from the model assumptions and unforeseen scenarios arise the business and the broader ecosystem evolve. The method and system disclosed in the embodiments herein facilitate generating simulation of various material replenishment scenarios based on a user input. The method and system further generates one or more recommendations for material replenishment, based on an optimization process carried out.

Abstract: Sourcing is a practice of locating and selecting entities based on set criteria. Determining most appropriate supplier entities at the lowest cost can develop a competitive advantage. However, existing sourcing techniques lack effective ways to target best suppliers for right part bundling and to efficiently optimize sourcing cost for sustained savings. Present disclosure leverages machine learning and optimization methods with technology data to provide a computationally efficient solution. Relationships between parts and corresponding attributes are obtained for parts bundling and best supplier locations are mapped for selected part bundles. A sourcing cost minimizer is used in conjunction with an iterative process to grow or limit supplier capacity by constraining award amount, bundle mix, or number of supplier entities based on multiple alternative scenarios being defined to systemically minimize cost and manage risks driven by changes in customer demand or manufacturing location.

Abstract: A system and method for collaborative product configuration optimization model. A plurality of product families and corresponding one or more product sub-families, a plurality of options families associated with each of the sub-product families is obtained. The option family includes one or more option variants. A first product family from the plurality of product families is selected and the one or more option variants of the first product family is associated with a reference value and is selected based on availability of the one or more option variants. A feasible configuration set for the selected first product family is generated by iteratively performing, for each of a unit of demand, a multi-constrained longest path search traversing across the plurality of option families in an non-increasing order of an average of the reference value of the plurality of the option families and a list of configurations is optimized based on the generated feasible configuration.