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US-20260127530-A1 - SYSTEM AND METHOD FOR INDUSTRIAL LABOR FORECASTING

US20260127530A1US 20260127530 A1US20260127530 A1US 20260127530A1US-20260127530-A1

Abstract

A method and system to forecast the labor required for an industrial or construction job based on industry standard job classifications and key job impact factors that affect the labor required to do a job. A new job description is created for a job and matched to an industry standard job classification which has an identification of details pertaining to the industry standard job. A historical job database provides a baseline estimate of the labor required to complete the job based on the new job requirements and the baseline estimate is adjusted to provide a more accurate labor estimate by incorporating the job impact factors that impact the labor required for the job. A work digest for the job can be created and provided to a worker.

Inventors

  • Ehsan Foroughi
  • Calvin Benchimol

Assignees

  • Crewscope Inc.

Dates

Publication Date
20260507
Application Date
20241104

Claims (20)

  1. 1 . A method for labor forecasting comprising: creating a new job record for a new job, the new job record comprising job specifications and having a classification identifier associated with an industry standard job record; identifying a plurality of historical job records in a historical job database having the same classification identifier as the new job record, each historical job record describing a historical job comprising historical job specifications specific to the historical job; in a labor forecasting engine, receiving the plurality of historical job records pertaining to the job classification identifier and creating a normalized labor forecast based on the plurality of historical job records; identifying one or more job impact factors associated with the industry standard job; and adjusting the normalized labor forecast for the new job record based on the job impact factors to provide an adjusted labor forecast.
  2. 2 . The method of claim 1 , wherein the industry standard job record comprises job requirements for the industry standard job.
  3. 3 . The method of claim 1 , wherein the classification identifier of the new job record is in a category or subcategory of each of the plurality of historical job records used to create the normalized labor forecast.
  4. 4 . The method of claim 1 , wherein the job is an industrial project, construction project, or industrial manufacturing.
  5. 5 . The method of claim 1 , further comprising querying a worker on details pertaining to the job impact factors.
  6. 6 . The method of claim 5 , further comprising incorporating the details pertaining to the job impact factors into the adjusted labor forecast.
  7. 7 . The method of claim 1 , further comprising creating a work digest relevant to the new job and communicating the work digest to a worker.
  8. 8 . The method of claim 7 , wherein the work digest comprises one or more of text, an image, audio, and video.
  9. 9 . The method of claim 7 , wherein the work digest provides information on one or more of job conditions, job requirements, job specifications, and job best practices for the new job.
  10. 10 . The method of claim 7 , wherein the work digest comprises generated text provided by a Large Language Model, and wherein the generated text reflects sentiments and tone to motivate the worker.
  11. 11 . The method of claim 7 , wherein the work digest comprises specific information about the new job and its progress.
  12. 12 . The method of claim 1 , wherein the job impact factors comprise one or more of weather, time of year, job location, soil or ground type where the job is located, humidity, temperature, surface water level, labor market, materials used, and equipment used.
  13. 13 . The method of claim 1 , further comprising, once the job is completed, adding the new job record as a new historical job record to the historical job database.
  14. 14 . The method of claim 1 , further comprising providing a worker with a goal for completing the job within a time allotment for the labor forecast, and rewarding the worker for completion of the job within the time allotment.
  15. 15 . A system for labor forecasting comprising: at least one processor coupled to one or more memory, the one or more memory comprising: a job classification database comprising a plurality of industry standard job records, each industry standard job record comprising a job description for an industry standard job and a job classification identifier; a historical job database comprising a plurality of historical job records, each historical job record describing a historical job associated one of the plurality of industry standard job record in the job classification database; a job generation engine for creating a new job record, the new job record comprising new job specifications and associated with one of the plurality of industry standard job records by the job classification identifier; and a labor forecasting engine for receiving the plurality of historical job records pertaining to the job classification identifier, creating a normalized labor forecast for the new job, and identifying one or more job impact factors associated with the job classification identifier, wherein the labor forecasting engine adjusts the normalized labor forecast for the new job based on the identified job impact factors to provide an adjusted labor forecast for the new job.
  16. 16 . The system of claim 15 , further comprising a peripheral device for querying a worker about the identified job impact factors and receiving details on the one or more job factors.
  17. 17 . The system of claim 15 , wherein the job impact factors comprise one or more of weather, time of year, job location, soil or ground type where the job is located, humidity, temperature, surface water level, labor market, materials used, and equipment used.
  18. 18 . The system of claim 15 , wherein the industry standard job record comprises job requirements for the industry standard job.
  19. 19 . The system of claim 15 , wherein the job classification identifier is in a category or subcategory of each of the plurality of historical job records used to create the normalized labor forecast.
  20. 20 . The system of claim 15 , wherein the industry standard job is an industrial project, construction project, or industrial manufacturing.

Description

FIELD OF THE INVENTION The present invention pertains to a system and method of forecasting the labor required for an industrial project based on worker input, job constraints, and machine learning based forecasting incorporating key job impact factors that have a significant effect on labor. BACKGROUND In construction and industrial manufacturing, and other similar sectors of industry, the cost of major projects and industrial production is typically estimated in advance of the project to determine the forecasted budget needed to deliver on the project or meet a production target. In construction projects, the goal or product is typically fixed, as determined by the drawings or job specifications, whereas the labor, or effort cost, is variable. In industrial manufacturing, such as, for example, mining, materials extraction, quarrying, oil and gas, and other extractive manufacturing, labor is typically fixed but output or production is variable, which is reflected in having permanent or fixed workers with fixed salaries and pre-determined shifts. The goal of a plant in industrial manufacturing is generally is to maximize output, and industrial manufacturing companies typically use labor estimates to accurately price their products for market. In a construction project the goal is to minimize labor hours to complete the project. In both cases, being able to accurately forecast the relationship between labor hours and output enables companies to create accurate estimates and fairly price their products and services. In construction, once the cost is estimated for a construction project, construction companies then bid for the project by leveraging the estimate and adding a desired profit margin as well as risk management paddings. Construction projects are generally awarded to a contractor after the contractor or construction company has prepared a bid for the project and the winning company is bound by the original bid to complete the project. To prepare a bid, the construction company attempts to estimate the cost of the project, including all material, tools, and labor costs, and adds on the desired profit margin, allowing flexibility for overages and contingencies. The estimated cost of any significant construction project needs to be determined accurately in advance of the project. In particular, a bid that is too high could result in failure to win the bid in a competitive bidding process, and a bid that is too low could result in a loss of profit with potentially significant losses. The cost of large construction projects and industrial manufacturing processes are generally estimated by breaking down the job into smaller components or jobs and estimating each component or job individually, where each component has cost contributions from labor, materials, and equipment. Afterward, the estimate of each of the components is added up, a project administration and management overhead is added, and a risk adjustment value is added to get the cost estimate. A target profit margin is then added to the cost estimate to calculate the bid or market price. The cost estimation of a construction project or industrial manufacturing process must include the labor cost, material cost, and equipment cost for the project, with accurate timing for each stage. Of these factors, material costs are generally straightforward to estimate and are often based on project plans and blueprints, with the amount of materials needed calculable from square footage measurements and materials costs taken from commercial suppliers. Typically, any change from material cost estimations may also be passed onto the project owner or worked into the estimate as external capital costs and have a smaller effect on the profitability of the project. Equipment costs are, in most cases, considered as part of the overhead cost of labor since equipment must be operated by workers and how long the equipment is needed is determined by how many hours will be worked. With knowledge of the labor cost the equipment cost can generally be accurately estimated based on the number days or hours the equipment will be required. In industrial manufacturing, predicting and hitting production output targets given a fixed amount of time and labor, such as amount of material produced per day, provides predictability to costing the resulting product. Labor estimates in industrial manufacturing can depend on various conditions. For example, in open quarries, weather can significantly impact production, with reductions in production of 20% or more on a rainy day compared to a sunny day. Other factors that can impact production numbers in extractive production include equipment availability and environment-related downtime. Accurate project estimation is, at present, a combination of art and science, and most often falls to skilled human project estimators. Typically, estimate professionals and project managers employed by construction and industrial companies estimate pr