Coordinated and optimized dispatching method for electric buses
US-2024428361-A1 · Dec 26, 2024 · US
US2016019484A1 · US · A1
| Field | Value |
|---|---|
| Publication number | US-2016019484-A1 |
| Application number | US-201414501123-A |
| Country | US |
| Kind code | A1 |
| Filing date | Sep 30, 2014 |
| Priority date | Jul 18, 2014 |
| Publication date | Jan 21, 2016 |
| Grant date | — |
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Systems and methods for managing resources in a project management model are described herein. In one embodiment, a computer-implemented resource management method is disclosed. The method comprises generating, for fulfilling a project specification, a resource allocation model indicative of at least one of: a hierarchical arrangement of a plurality of resource entities, or a competency index of one or more of the resource entities. One more project phases capable of being automated are identified by analyzing the project specification using one or more automation rules. The method includes initiating computational processing by a bot for automating the identified one or more project phases, and generating a modified workbench for at least one of the resource entities based on the resource allocation model and the identified one or more project phases.
Opening claim text (preview).
1 . A computer-implemented resource management method, comprising: generating, based on a project specification, a resource allocation model indicative of a hierarchical arrangement of a plurality of robotic resource entities; determining, by the resource allocation model, a plurality of competency parameters associated with one or more of the plurality of robotic resource entities and a competency index for the one or more robotic resource entities based on corresponding plurality of competency parameters; identifying one or more project phases capable of being automated, by analyzing the project specification using a parser and natural language processor, wherein the project specification comprises unstructured data; initiating computational processing for automating the identified one or more project phases; and generating a modified workbench for at least one of the robotic resource entities based on the resource allocation model and the automated one or more project phases. 2 . The method of claim 1 , wherein identifying further comprises using one or more automation rules comprising at least one of: cognitive analytics rules, continuous integration rules, or bot implementation rules on the project specifications. 3 . The method of claim 1 , wherein the method further comprises: assigning a role for at least one of the robotic resource entities associated with the resource allocation model; and assigning one or more project tasks to that at least one robotic resource entity based on the assigned role. 4 . The method of claim 1 further comprising: determining whether a project task is to be assigned to one of a robotic resource and a human resource; ascertaining an implementation success ratio of the robotic resource on the task to be assigned; and overriding allocation of the task to the robotic resource on ascertaining the implementation success ratio to be below a pre-defined threshold. 5 . The method of claim 1 , wherein the method further comprises: identifying one or more project-related processes having an effectiveness index less than a pre-defined threshold; modifying the identified one or more project-related processes based on at least one of: lean techniques or six sigma techniques, wherein modifying the identified one or more project-related processes increases the effectiveness index to equal or exceed the pre-defined threshold; and modifying the resource allocation model in response to modifying the identified one or more project-related processes. 6 . A project resource management system, comprising: one or more hardware processors; one or more memory units communicatively coupled to the one or more processors, wherein the one or more memory units store processor-executable instructions, which, on execution, cause the one or more processors to perform acts comprising: generating, based on a project specification, a resource allocation model indicative of a hierarchical arrangement of a plurality of robotic resource entities; determining, by the resource allocation model, a plurality of competency parameters associated with one or more of the plurality of robotic resource entities and a competency index for the one or more robotic resource entities based on corresponding plurality of competency parameters; identifying one or more project phases capable of being automated, by analyzing the project specification using a parser and natural language processor, wherein the prosect specification comprises unstructured data; initiating computational processing for automating the identified one or more project phases; and generating a modified workbench for at least one of the robotic resource entities based on the resource allocation model and the automated one or more project phases. 7 . The system of claim 6 , wherein the instructions, on execution, further cause the processor to perform acts comprising using one or more automation rules comprises at least one of: cognitive analytics rules, continuous integration rules, or bot implementation rules. 8 . The system of claim 6 , wherein the instructions, on execution, further cause the processor to perform acts comprising: assigning a role for at least one of the robotic resource entities associated with the resource allocation model; and assigning one or more project tasks to that at least one robotic resource entity based on the assigned role. 9 . The system of claim 6 , wherein the instructions, on execution, further cause the processor to perform acts comprising: determining whether a project task is to be assigned to one of a robotic resource and a human resource; ascertaining an implementation success ratio of the robotic resource on the task to be assigned; and overriding allocation of the task to the robotic resource on ascertaining the implementation success ratio to be below a pre-defined threshold. 10 . The system of claim 6 , wherein the instructions, on execution, further cause the processor to perform acts comprising: identifying one or more project-related processes having an effectiveness index less than a pre-defined threshold; modifying the identified one or more project-related processes based on at least one of: lean techniques or six sigma techniques, wherein modifying the identified one or more project-related processes increases the effectiveness index to equal or exceed the pre-defined threshold; and modifying the resource allocation model in response to modifying the identified one or more project related processes. 11 . A non-transitory computer-readable device, storing computer-executable resource management instructions, comprising instructions for: generating, based on a project specification, a resource allocation model indicative of a hierarchical arrangement of a plurality of robotic resource entities; determining, by the resource allocation model, a plurality of competency parameters associated with one or more of the plurality of robotic resource entities and a competency index for the one or more robotic resource entities based on corresponding plurality of competency parameters; identifying one or more project phases capable of being automated, by analyzing the project specification using a parser and natural language processor, wherein the project specification comprises unstructured data; initiating computational processing for automating the identified one or more project phases; and generating a modified workbench for at least one of the robotic resource entities based on the resource allocation model and the automated one or more project phases. 12 . The device of claim 11 , wherein identifying further comprises using one or more automation rules comprises at least one of: cognitive analytics rules, continuous integration rules, or bot implementation rules. 13 . The device of claim 11 , the resource management instructions further comprising instructions for: assigning a role for at least one of the robotic resource entities associated with the resource allocation model; and assigning one or more project tasks to that at least one robotic resource entity based on the assigned role. 14 . The device of claim 11 , the resource management instructions further comprising instructions for: determining whether a project task is to be assigned to one of a robotic resource and a human resource; ascertaining an implementation success ratio of the robotic resource on the task to be assigned; and overriding allocation of the task to the robotic resource on ascertaining the implementation success ratio to be below a pre-defined threshold. 15 . The device of c
Resource planning in a project environment · CPC title
Staff planning in a project environment · CPC title
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