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WO2018199731A1 - Système interactif pour améliorer la productivité du travail dans des processus de manufacture - Google Patents

Système interactif pour améliorer la productivité du travail dans des processus de manufacture Download PDF

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Publication number
WO2018199731A1
WO2018199731A1 PCT/MX2017/000050 MX2017000050W WO2018199731A1 WO 2018199731 A1 WO2018199731 A1 WO 2018199731A1 MX 2017000050 W MX2017000050 W MX 2017000050W WO 2018199731 A1 WO2018199731 A1 WO 2018199731A1
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WO
WIPO (PCT)
Prior art keywords
production
clause
parameters
interactive system
productivity
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Ceased
Application number
PCT/MX2017/000050
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English (en)
Spanish (es)
Inventor
Fernando MIJARES GARCÍA
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Individual
Original Assignee
Individual
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Individual filed Critical Individual
Priority to PCT/MX2017/000050 priority Critical patent/WO2018199731A1/fr
Publication of WO2018199731A1 publication Critical patent/WO2018199731A1/fr
Anticipated expiration legal-status Critical
Ceased legal-status Critical Current

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Classifications

    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B19/00—Programme-control systems
    • G05B19/02—Programme-control systems electric
    • G05B19/418—Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS] or computer integrated manufacturing [CIM]
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
    • Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
    • Y02P90/02—Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
    • Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
    • Y02P90/80—Management or planning

Definitions

  • the present invention applies to manufacturing processes and work activities where the real-time measurement of the efficiency of available labor is a relevant factor to meet the production objectives, or, in the measurement of the productive efficiency of Semi-automatic machinery of fully automated production lines.
  • Some examples of inventions related to monitoring and improving labor productivity are:
  • a monitoring system comprising computer terminals at each workstation for data exchange, a monitoring center that communicates with the terminals; a server that collects, processes and analyzes the data collected from the terminals.
  • V Data transmission wirelessly using a certain frequency band
  • Vf The method of implementing the monitoring system, which considers the installation of terminals, the capture of information, data transmission, data processing and calculation of salaries based on the productivity data collected from each terminal.
  • the system proposed in this patent is limited to exchange data and process the production of each worker for the purpose of calculating the payment of wages based on individual productivity.
  • the main limitations with respect to our invention is that said system suggests the possible capabilities of this monitoring system to monitor production, but without clearly stating the embodiment to obtain said system capabilities, which still leaves the problem unresolved. in the background that represents the uncertainty of the multiple individual decisions of workers that can result in the capture of erroneous information.
  • a hierarchical method is mainly drafted to determine the causal relationship of a production system and provide a comprehensive productivity analysis for that system. The method considers the following steps:
  • the method proposed by this patent although it helps to diagnose manufacturing processes and propose efficient systems, does not solve the need to correct the inefficiencies of a productive process in a timely manner at the moment when the progress of production is being negatively offset Regarding the production plan. Nor does it resolve the identification of the individual labor behaviors or deficiencies of the workers at each work station.
  • the system we propose is novel because it focuses on integrating a system and at least one method with different characteristics, focused on detecting and immediately addressing negative gaps that affect compliance with the plans of production, and identify needs to improve individual labor skills for each production process required for each specific production plan.
  • Figure 1 shows the general diagram of the system that shows the sequence to establish the different parameters (i) that allow to configure the programming of the production plan (le) according to the production parameters (la) and the parameters of workers and their competences (Ib).
  • Figure 2 shows the configuration flow of the production program (le) in the console from a work order (2) subdMad in wagons (2a) and the decision processes according to the recovery time (le) and the deviations of productivity (Id) presented by the work stations (2b) and the parts produced.
  • Figure 3 shows the configuration of parameters by competences (Ib) of the workforce assignable to the production of a specific work order (2), with the decision takers based on the certifications of each worker.
  • Figure 4 shows the typical configuration flow of a tablet (4a) for its connection with the sensors of a production line, the sending of data to the console (4b) and synchronization with the server (4c).
  • Figure 5 shows the flow to display the projected production parameters (la) corresponding to a workstation (2b) on a tablet (4a).
  • Figure 6 shows a diagram of the general flow of an example of assignment of a work order (2) in wagons (2a) and how they are assigned to a tablet (4a) in a workstation (2b) so that it can be consulted by the worker assigned to said workstation (2b).
  • Figure 7 represents the interaction of the workers with the system through the tablets (4a) in the work stations (2b) to carry out the production corresponding to a wagon (2a).
  • Figure 8 Represents the way in which the system interacts with the sensors (8a) installed in a production line to automatically feed the production progress, analysis of production data and shutdowns.
  • Figure 9 shows a diagram of the workforce allocation flow within the system according to the needs of a production plan, shifts, overtime and required skills.
  • the interactive system to improve the productivity that we propose here, integrates a sequence of processes specially designed to, on a first piano, analyze and direct the planned production of productive activities in manufacturing environments.
  • production is projected based on quantities and times taking into account a wide variety of factors such as availability of available productive hours, breaks, scheduled and unscheduled stoppages, efficiencies and capacity to the teams and tools, labor competencies and individual behaviors of each worker, to elaborate a realistic production plan.
  • this system directs the production plan guiding those involved and showing in an interactive way what must be happening at each moment in each of the work areas where the production is carried out.
  • this system receives real-time information from the production area, yielding the result of production progress at the moment the process is taking place.
  • the system has elements to analyze the information received from the production area and calculate variables and yields, permanently compared to the production plan, providing feedback to each worker with real-time information on their productivity, compared to the program. of production and offering the possible actions to align your productivity with the production plan and the available time of the day.
  • the human factor in terms of individual skills is one of the most significant variables that can improve or impair productivity.
  • the system proposed here has a human resources module that integrates competencies, skills, training and certifications for each person monitored through the system. This module is integrated into the productive system and validates if the workers in the productive area have the necessary skills and knowledge to be able to properly execute the required work in a timely manner, sending immediate feedback on inefidends detected in the productive system, due to staff with lack of skills and / or knowledge.
  • the system can issue an alert, including the configuration so that the system blocks the assignment of non-competent workers to workstations.
  • the system calculates performance values of each worker for each day of production, generating a database in which, through statistical processing of said data, a reasonably reliable value of the performance and productive capacity of each worker is obtained.
  • this system as it is implemented in different manufacturing companies located in the same area or region, delimited in some way by the availability and mobility of the same labor supply, allows feeding a centralized database of All workers who have interacted with the system from different companies or production centers, generating an individual history of each of these workers, about their productive efficiency, technical skills, quality and fulfillment of their individual production goals, favoring access To this information the process of selecting the best available workforce in the area or region where the system has been implemented.
  • the system has a module in which not so obvious changes in the behavior of the equipment are monitored, such as energy consumption, temperature, air flows, water, oil, etc., to have a historical comparison of production output against energy inputs or equipment behavior and to be able to detect if under the same parameters the behavior changes, activating said system module by means of alerts and signals predicting a possible future failure, to anticipate it and avoid it with pre-ovo or preventive maintenance.
  • the system stores the information of each maintenance generating a historical record of said maintenance.
  • This type of device is ideally an electronic tablet (4a) with a touch screen mounted on a support located in a place inside the workstation (2b), where ergonomically and visually it does not make it difficult for the worker to interact with said device, thereby interrupting The production process.
  • the tablet (4a) is wirelessly linked to sensors (8a) that detect the flow of a produced or assembled part by the worker, automatically capturing in the tablet program (4a) each piece produced or assembled and the moment in which said process occurs. Or, manually the worker can have access to a button, which every time he presses it sends a signal to the tablet (4a) to count a piece produced or assembled each time that button is pressed.
  • This arrangement of electronic tablets (4a) can be configured for a production line or for all areas of a manufacturing company where there is a production process that can be counted as sub processes or sub assemblies made by the workers as part of compliance with the production plan (le). Once all the electronic tablets (4a) necessary to monitor and interact with the workers of a manufacturing line or center are installed, each of said tablets is linked (4a) to a central console (4b) specially designed for this interactive system.
  • Said central console (4b) receives and concentrates the information of each tablet (4a) installed in the line or manufacturing center and in turn connects with a production management computer (4c), from where the specific parameters are configured ( 1), according to the production plan (le), the available workforce (Ib) and the capacity of the equipment and the logistics of supply of Insumes, transport of parts in process, work schedules, among other variables that allow measure the efficiency of each production plan (le).
  • the production management computer (4c) is in turn linked to a master server (4d), which is a remote server where the computer platform that allows each production management computer (4c) is installed. , with permissions to link to the system, access the functionalities required for the configuration of production parameters (la), activate and deactivate access to electronic tablets (4a) at workstations (2b), register and lowers individual users of electronic tablets (4a), as well as access to results and statistics processed with the data collected by each electronic tablet (4a), related to the activity of each active worker in the system.
  • master server (4d) which is a remote server where the computer platform that allows each production management computer (4c) is installed.
  • the general configuration comprises three main aspects, the production parameters (the), the equipment maintenance parameters (Id) and the labor competency parameters (Ib).
  • the production parameters (la) are configured by giving values to each production variable that contemplates the production plan (le).
  • the main variables in a common manufacturing process are: number of parts to be produced, number of sub processes or sub assemblies, total time, available workers, effective man-hours, parts to be produced per unit of time, duration, number of scheduled shutdowns and of unscheduled stoppages, among others, that the person responsible for the production plan (le) determines based on their experience and knowledge about the manufacturing process to be carried out.
  • the values that determine the equipment maintenance parameters (Id) are established. These parameters are defined for preventive and predictive maintenance that will allow in the system programming to determine the indicated time and carry out stoppages for maintenance of the equipment before it presents failures or its work efficiency falls below the parameters linked to the efficiency requirements to achieve the production goal. To achieve this early detection of future failures in the equipment, the system issues alerts when deviations occur in the efficiency parameters of any equipment that is part of a production line monitored by the system.
  • the labor competency parameters (Ib) are established, to ensure that each worker available in the production process has the knowledge and skills necessary to achieve the efficiency and quality required in the plan of production.
  • the labor competency parameters (Ib) begin with the reference given by the profiles of each position specified by the human resources area (see Fig. 9). With the reference of the profiles, a breakdown or matrix of technical and labor competencies aligned to training, training and evaluation programs is performed to certify each worker in the competences achieved. The competences are defined in turn by the technical production requirements of the parts, pieces or assemblies established in each work order (2).
  • the next step in the process is to program these parameters so that each of the devices that make up the system performs the corresponding functionality according to said programming.
  • the first indispensable programming is the production plan (le), which in real practice begins with a work order (2), in which the production programmer demands a certain number of pieces and a required delivery date.
  • the design of the production plan (le) in the system considers the available resources and the definition of the values of the parameters of each slope of the system to estimate the effective man-hours of work in relation to the installed capacity and clearances to achieve total production of the work order (2) within the required period.
  • the work order (2) or the demand that starts the process is divided into sub orders or production wagons (2a).
  • These wagons (2a) allow disaggregating the total order and distributing it according to the available labor resources and the production capacity of the equipment involved in the production plan (le).
  • the amount of effective production hours necessary to complete each car (2a) is calculated. This calculation is based on the variables "standard cycle” and “recovery time”, generating multiples of said calculations according to the number of wagons (2a) or sub-orders in which the entire order was divided.
  • each wagon (2a) generating a waiting queue of wagons (2a) that according to the pre-established parameters, will allow to project and compare, within shorter periods, the real advance against the advance programmed in the system to meet the production plan (le) determined for each work order (2).
  • the monitoring by the system on the progress of production compared to the projected productivity, identifies at all times the productivity deviations (2d) that may occur by work station or by manufactured part.
  • the detection of productivity deviations (2d) is measured by assigning the wagons (2a) in the waiting queue to the available work stations (2b) and according to the production progress presented by each work station (2b).
  • a wagon (2a) of the waiting queue is assigned to a workstation (2b)
  • the information collected by the electronic tablets (4a) is sent in real time to the central console (4b) and processed said information on the master server (4d), to first detect recovery times (2c) per workstation and per part.
  • recovery times do not occur in a workstation (2b), the system applies recovery times of the parts.
  • the system applies recovery times from the workstation (2b). If both the work stage (2b) and the parties have recovery times (2c), the system offers the person in charge of the production plan the option of choosing one of the two recovery times or performing a combination of both, to achieve A more realistic projection. This process is continuously carried out by the system to detect active productivity deviations (2d) at the moment they occur.
  • a car (2a) can be assigned to the work stage (2b), said car (2a) being placed at the end of the waiting queue of said work station (2b).
  • the calculation of recovery times and active deviations allows the system to estimate the effective hours and the corresponding work volumes that this car (2a) will take to be produced, indicating in the system the start time and end time for the production of each car (2a), and the person in charge of the production plan can assign and reallocate wagons (2a) to the waiting positions and the work stations (2b) that best suits to meet the total production in the required period.
  • the system updates the production balances and the projection of hours based on the production since the last update of the system or that modifications have been made to the initial parameters (1) .
  • the system After each update of the production balance, the system identifies the occurrence of new productivity deviations in the wagons (2a) assigned to each work stage (2b) so that they can be ratified in the production line or at the specific station where deviation occurs (2d).
  • the person responsible for the production plan may decide to make unscheduled shutdowns, for maintenance, staff rest or other circumstances. These stops can be carried out for the entire production process or for a specific station (2b).
  • the system When performing the production plan (le) related to a work order (2), the system allows the person in charge of the production plan to efficiently assign the necessary workers to comply in time with the delivery of the order (2).
  • This assignment includes the identification of the workforce available for both ordinary work shifts and overtime that must be worked to achieve the production plan (le).
  • the available workforce is fed into the system under the parameters of competencies and individual productivity (Ib) when registering the certifications of each worker as well as their productivity and efficiency, measured by the statistical results of the individual performance that the system registers and accumulates Each worker

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Abstract

L'invention concerne un système interactif pour améliorer l'efficacité de main-d'oeuvre dans des processus de manufacture faisant intervenir la définition de paramètres de production, de compétences professionnelles et d'entretien d'équipement, une console centrale reliée à des dispositifs électroniques installés dans des postes de travail, traitant des bases de données de productivité du travail, et des capteurs pour comptabiliser la production dans les lignes de production surveillées par le système en temps réel pendant le processus de production, détectant des anomalies dans la mise en oeuvre du plan de production.
PCT/MX2017/000050 2017-04-25 2017-04-25 Système interactif pour améliorer la productivité du travail dans des processus de manufacture Ceased WO2018199731A1 (fr)

Priority Applications (1)

Application Number Priority Date Filing Date Title
PCT/MX2017/000050 WO2018199731A1 (fr) 2017-04-25 2017-04-25 Système interactif pour améliorer la productivité du travail dans des processus de manufacture

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
PCT/MX2017/000050 WO2018199731A1 (fr) 2017-04-25 2017-04-25 Système interactif pour améliorer la productivité du travail dans des processus de manufacture

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WO2018199731A1 true WO2018199731A1 (fr) 2018-11-01

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Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN111190400A (zh) * 2019-12-30 2020-05-22 中山路得斯空调有限公司 一种基于文字图形广播的生产线交互系统
CN117313983A (zh) * 2023-08-31 2023-12-29 华能核能技术研究院有限公司 一种核电厂基于工单系统的设备管理方法及系统
US11874647B2 (en) * 2022-04-14 2024-01-16 Chengdu Qinchuan Iot Technology Co., Ltd. Industrial internet of things system for controlling production line parameter and control methods thereof

Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP2801941A1 (fr) * 2013-05-09 2014-11-12 Rockwell Automation Technologies, Inc. Utilisation de données en nuage pour la virtualisation d'un environnement d'automatisation industrielle avec des superpositions d'informations
US20170031354A1 (en) * 2015-07-29 2017-02-02 General Electric Company Methods, systems, and apparatus for resource allocation in a manufacturing environment

Patent Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP2801941A1 (fr) * 2013-05-09 2014-11-12 Rockwell Automation Technologies, Inc. Utilisation de données en nuage pour la virtualisation d'un environnement d'automatisation industrielle avec des superpositions d'informations
US20170031354A1 (en) * 2015-07-29 2017-02-02 General Electric Company Methods, systems, and apparatus for resource allocation in a manufacturing environment

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
"Operations Management & Information Systems - Intermediate", GROUP II/PAPER-9. PRODUCTION PLANNING QUALITY MANAGEMENT OPERATIONS INFORMATION SYSTEMS ERP, 30 November 2014 (2014-11-30), pages 2.21, 2.35, 2.43 - 2.51, 2.109, 2.147, 2.277-2.278, 3.19, 6.10-6.11,, Retrieved from the Internet <URL:http://icmai.in/uploadlStudents/Syllabus-2012/Study_Material_New/Inter-Paper9.pdf> [retrieved on 20171128] *

Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN111190400A (zh) * 2019-12-30 2020-05-22 中山路得斯空调有限公司 一种基于文字图形广播的生产线交互系统
US11874647B2 (en) * 2022-04-14 2024-01-16 Chengdu Qinchuan Iot Technology Co., Ltd. Industrial internet of things system for controlling production line parameter and control methods thereof
CN117313983A (zh) * 2023-08-31 2023-12-29 华能核能技术研究院有限公司 一种核电厂基于工单系统的设备管理方法及系统

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