Systems and methods for supply chain design and analysis

• US 10,108,916 B2
• Filed: 08/22/2013
• Issued: 10/23/2018
• Est. Priority Date: 08/16/2013
• Status: Active Grant

• Current Assignee: TATA Consultancy Services Limited (Tata Sons Pvt Ltd.)
• Original Assignee: TATA Consultancy Services Limited (Tata Sons Pvt Ltd.)
• Inventors: Bhowmik, Amit, Sardar, Gautam
• Primary Examiner(s): Gills, Kurtis
• Application Number:
  US13/973,734
• Publication Number:
  US 20150051940A1
• Time in Patent Office: 1,888 Days
• Field of Search: 705 725
• CPC Class Codes: G06Q 10/06315 Needs-based resource requirements planning or analysis

Abstract

Systems and methods for supply chain design and analysis to optimize costs associated with a supply chain are described. According to an embodiment, the supply chain management system comprises a data extraction module, an analysis module, and a presentation module coupled to a processor. The data extraction module obtains supply chain data from one or more data sources. The analysis module analyzes a plurality of parameters and at least one future state map to ascertain at least one business scenario. Further, the analysis module identifies flow constraints in the at least one business scenario based on a flow analysis. Further, the analysis module selects decision parameters from amongst the plurality of parameters based on the flow constraints and a simulation feedback. Further, the analysis module simulates at least one experimental design based on the decision parameters. Furthermore, the presentation module generates, a plurality of maps based on visual analytics.

Claims

1. A system for design and analysis of a supply chain, wherein the system comprises:

a processor;

a data extraction module coupled to the processor to obtain supply chain data and scenario data from one or more data sources, wherein the supply chain data is indicative of supplier data and bill of material, warehouse and transport data, demand data, and production and site specific data, and wherein the scenario data is obtained based on user inputs about process involved in a supply chain;

an analysis module coupled to the processor to,

obtain value stream maps of the supply chain data and the scenario data, wherein the value stream maps are indicative of a lean manufacturing technique used to analyze and design the flow of materials and information needed to bring a product or service to a consumer;

determine a plurality of parameters and future state maps based on the value stream maps and ascertain one or more business scenarios based on the plurality of parameters, and the future state maps, wherein the plurality of parameters are indicative of factors that have influence on decisions related to the supply chain, and wherein the business scenarios are indicative of a realization of the supply chain;

identify, based on a flow analysis, flow constraints in the one or more business scenarios;

select decision parameters from the plurality of parameters based on the flow constraints and a simulation feedback, wherein the simulation feedback is obtained from previous simulations of a plurality of business scenarios and the simulation feedback is used for refining the selection of the decision parameters and the flow constraints, and wherein the decision parameters are indicative of parameters needed for simulation of the at least one business scenario for optimal supply chain design and analysis; and

simulate at least one experimental design based on the decision parameters for optimizing cost using a cost model associated with the supply chain, wherein the at least one experimental design is generated based on combinations of the one or more business scenarios and network analysis, wherein the simulation performed on a parameterized scenario and focused on the selected decision parameters enables increased speed of design of experiments and simulations thereof, and the resulting supply chain design is optimal for at least the selected refined decision parameters, wherein the experimental design and simulations enables tuning of the supply chain design and analysis to varying market conditions, wherein the simulation is a discrete simulation or a continuous simulation depending on type of industry for which the design and analysis of supply chain is conducted wherein the cost includes operating expenses, capital expenditures, and working capital of the supply chain; and

perform a regression analysis on results obtained after simulating the at least one experimental design to determine a regression model based on correlations between the plurality of parameters including the decision parameters and the cost model wherein the analysis module further comprises a parameterization module to;

determine a current state of the supply chain based on the supply chain data obtained from the one or more data sources, wherein the current state is indicative of current working of the supply chain;

identify the plurality of parameters by analyzing the current state and the scenario data;

create the at least one future state map of the supply chain based on the value stream mapping of the current state and the plurality of parameters; and

ascertain the at least one business scenario by analyzing the at least one future state map and the scenario data; and

a presentation module coupled to the processor to generate, based on visual analytics, a plurality of maps to depict at least one of a network flow, a process flow, the decision parameters, and costs associated with the supply chain.

2. The system as claimed in claim 1, wherein the scenario data includes cost details, material flow patterns and restrictions, process flows, and site constraints.

3. The system as claimed in claim 1, wherein the analysis module further comprises a flow and network analysis (FNA) module to,

execute the flow analysis on the one or more business scenarios;

and

identify the flow constraints from the one or more business scenarios based on the flow analysis.

4. The system as claimed in claim 3, wherein the flow and network analysis module executes a network analysis on the one or more business scenarios to optimize resources of multiple enterprises present in the supply chain.

5. The system as claimed in claim 1, wherein the simulation module provides the simulation feedback to the flow and network analysis module.

6. The system as claimed in claim 1, wherein the simulation module changes values of the decision parameters upon receiving the user input, and re-determines the cost associated with the supply chain based on the regression model.

7. A method for design and analysis of a supply chain, wherein the method comprises:

obtaining, by the processor, supply chain data and scenario data from one or more data sources, wherein the supply chain data is indicative of supplier data and bill of material, warehouse and transport data, demand data, and production and site specific data, and wherein the scenario data is obtained based on user inputs about process involved in a supply chain;

determining a current state of the supply chain based on the supply chain data obtained from the one or more data sources, wherein the current state is indicative of current working of the supply chain;

obtaining, by the processor, value stream maps of the supply chain data and the scenario data, wherein the value stream maps are indicative of a lean manufacturing technique used to analyze and design the flow of materials and information needed to bring a product or service to a consumer;

determining, by the processor, a plurality of parameters and future state maps based on the value stream maps, and ascertaining one or more business scenarios based on the plurality of parameters and the future state maps, wherein the plurality of parameters are indicative of factors that have influence on decisions related to the supply chain, and wherein the business scenarios are indicative of a realization of the supply chain;

identifying the plurality of parameters by analyzing the current state and the scenario data;

creating the future state maps of the supply chain based on the value stream mapping of the current state and the plurality of parameters;

ascertain the one or more business scenarios by analyzing the at least one future state map and the scenario data;

identifying, by the processor, based on a flow analysis, flow constraints in the one or more business scenarios;

selecting, by the processor, decision parameters from the plurality of parameters based on the flow constraints and a simulation feedback, wherein the simulation feedback is obtained from previous simulations of one or more business scenarios and the simulation feedback is used for refining the selection of the decision parameters and the flow constraints, and wherein the decision parameters are indicative of parameters needed for simulation of the at least one business scenario for optimal supply chain design and analysis;

simulating, by the processor, at least one experimental design based on the decision parameters for optimizing cost using a cost model associated with the supply chain, wherein the at least one experimental design is generated based on combinations of the one or more business scenarios and network analysis, wherein the simulation is performed on parameterized scenario and focused on the selected decision parameters enables increased speed of design of experiments and simulations thereof, and the resulting supply chain design is optimal for at least the selected refined decision parameters, wherein the experimental design and simulations enables tuning the supply chain design and analysis to varying market conditions, wherein the simulation is a discrete simulation or a continuous simulation depending on type of industry for which the design and analysis of supply chain is conducted;

wherein the cost includes operating expenses;

capital expenditures; and

working capital of the supply chain;

performing, by the processor, a regression analysis on results obtained after stimulating the at least one experimental design to determine a regression model based on correlations between the plurality of parameters including the decision parameters and the cost model; and

generating, by the processor, based on visual analytics, a plurality of maps to depict at least one of a network flow, a process flow, the decision parameters, and costs associated with the supply chain.

8. The method as claimed in claim 7 wherein the scenario data includes cost details, material flow patterns and restrictions, process flows, and site constraints.

9. The method as claimed in claim 7 further comprises executing a network analysis on the one or more business scenarios to optimize resources of multiple enterprises present in the supply chain.