Workshop production process radio frequency identification tracking management system

Abstract

The invention relates to the technical field of workshop production, and discloses a workshop production process radio frequency identification tracking management system, which monitors products through an RFID tag, an antenna and an RFID reader-writer, and then sends data to an RFID rear-end system, the RFID rear-end system is connected with a production data monitoring module through a network, and the production data monitoring module is connected with the production data monitoring module through a network. A plurality of groups of data in production are collected and numbered to form a plurality of data sets, a production data analysis module calculates production equipment abnormity evaluation SYpg, production evaluation SCpg and actual production number SJsc according to the plurality of data sets, compares the values with corresponding threshold values, judges whether an abnormal condition exists or not, and sends the abnormal condition to a data processing module. When a problem occurs, a signal is sent to the abnormity alarm module, so that the position and the state of a product can be tracked in real time, the smooth proceeding of the production process is ensured, meanwhile, the equipment abnormity is evaluated, the problem is quickly found, the current production progress condition is clearly known, and an alarm is given when the abnormity is found.

Description

Technical Field

[0001] The invention relates to the technical field of workshop production, and in particular to a radio frequency identification tracking and management system for workshop production processes. Background Art

[0002] The workshop production process is the core link of an enterprise's manufacturing products. It covers the entire process from the input of raw materials to the output of finished products, involving multiple delicate and interrelated steps. First, the raw materials are purchased and inspected according to the production plan to ensure that the quality of the raw materials meets the standards. These qualified raw materials are then stored in the warehouse and managed in an orderly manner. A detailed production plan is then formulated to clarify production tasks, batches and progress, and the production equipment is comprehensively inspected and debugged to ensure the smooth operation of the production line. Then processing, such as cutting and molding, is carried out to transform the raw materials into semi-finished products or components. The workshop production process is a complex and delicate process, which requires close collaboration among all links to ensure the orderly progress of the production process and the stable and reliable product quality. Through scientific production planning, strict quality control and continuous improvement and optimization, enterprises can continuously improve production efficiency and product quality, meet market demand and obtain better economic benefits.

[0003] In the traditional production model, the transmission of information often relies on manual recording and input, which is not only inefficient but also prone to errors and omissions. At the same time, it is impossible to accurately estimate the equipment and production conditions in the production process, which will seriously affect the execution of production plans and the control of product quality. Summary of the invention

[0004] 1. Technical issues to be resolved

[0005] In view of the deficiencies in the prior art, the present invention provides a workshop production process radio frequency identification tracking and management system, which can track the location and status of products in real time, ensure the smooth progress of the production process, effectively evaluate equipment abnormalities, quickly discover abnormalities, and promptly repair the equipment to restore the equipment to normal operation as soon as possible, thereby ensuring the continuity and stability of production. It can clearly understand the progress of the current production, and when a deviation is found between the actual production volume and the planned progress, it can take corresponding measures to make adjustments in a timely manner.

[0006] (II) Technical solution

[0007] To achieve the above-mentioned purpose, the present invention provides the following technical solutions: a workshop production process radio frequency identification tracking and management system, including an RFID management system, a production data monitoring module, a production data analysis module and an abnormal alarm module;

[0008] The RFID management system includes an RFID tag, an antenna, an RFID reader and an RFID back-end system. The RFID tag is used to be attached to the surface of the product to identify and record the product. The antenna is used to transmit radio frequency signals between the reader and the tag. The RFID reader is used to read the tag information and send it to the RFID back-end system. The RFID back-end system is connected to the production data monitoring module through the network.

[0009] The production data monitoring module collects the location data of multiple products through the RFID backend system and forms production process data, collects the production data of products by connecting to the workshop production system, and collects the production influencing factor data by connecting to the network and the production machinery system. The production data monitoring module numbers multiple production process data to form a product process data set SXj, numbers multiple product production data to form a product production data set CSj, and numbers multiple production influencing factor data to form a production influencing factor data set YXj. The production data monitoring module sends the above data sets to the production data analysis module;

[0010] The production data analysis module calculates the production equipment abnormality evaluation SYpg, the production evaluation SCpg and the actual production number SJsc according to the product process data set SXj, the product production data set CSj and the production influencing factor data set YXj;

[0011] The production data analysis module compares the production equipment abnormality assessment SYpg, the actual production number SJsc with the corresponding threshold value to determine whether there is an abnormality, and sends a signal to the abnormal alarm module if a problem occurs;

[0012] The abnormal alarm module performs corresponding early warning processing according to the corresponding signal.

[0013] Preferably, the product process data set includes multiple processes in the product production process, and the expression of the product process data set is as follows:

[0014]

[0015] in, Represents the first process of production in the product process data set. Represents the last process produced in the product process data set. The subscript n represents that there are n processes in total for the current product, and the superscript s represents the production time of the current process.

[0016] Preferably, the product production data set includes production completion volume, production processing time, and production qualification rate. The expression of the product production data set is as follows:

[0017] CSj={WCsc、JGSj、SChg}

[0018] Among them, WCsc represents the production completion volume in the product production data set, JGsj represents the production processing time in the product production data set, and SChg represents the production qualification rate in the product production data set.

[0019] Preferably, the production influencing factor data set includes a personnel impact rate, an equipment failure rate, and a production impact rate, and the production influencing factor data set is expressed as follows:

[0020] YXj={RYyx、SBgz、SCyx}

[0021] Among them, RYyx represents the personnel impact rate in the production influencing factor data set, SBgz represents the equipment failure rate in the production influencing factor data set, and SCyx represents the production impact rate in the production influencing factor data set.

[0022] Preferably, the calculation formula of the production equipment abnormality assessment SYpg is as follows:

[0023]

[0024] In the above formula, Represents the total number of the vth aging of the i-th process and the aging after the vth aging of the i-th process in the product process data set, It represents the total number of the vth aging of the ith process in the product process data set and the aging before the vth aging of the ith process, 2s means the difference is calculated twice, and PJrc is the tolerance value of the aging difference of all processes in the product process data set.

[0025] Preferably, the calculation formula for the production evaluation SCpg is as follows:

[0026]

[0027] In the above formula, Z represents the total orders produced.

[0028] Preferably, the calculation formula of the actual production number SJsc is as follows:

[0029] SJsc=(RYyx*τ+SBgz*σ+SCyx*ρ)*SCpg

[0030] In the above formula, τ represents the weight of the personnel impact rate in the production influencing factor data set, σ represents the weight of the equipment failure rate in the production influencing factor data set, and ρ represents the weight of the production impact rate in the production influencing factor data set.

[0031] Preferably, a production equipment abnormality threshold is set inside the production data analysis module. When the production equipment abnormality assessment SYpg is greater than the production equipment abnormality threshold, it is judged that the corresponding equipment of the current process has an abnormality, and an equipment abnormality signal is sent to the abnormal alarm module.

[0032] Preferably, an actual production threshold is set inside the production data analysis module. When the actual production number SJsc is less than the actual production threshold, it is determined that the current production efficiency is abnormal, and a production abnormality signal is sent to the abnormal alarm module.

[0033] Preferably, when the abnormal alarm module receives an equipment abnormality signal, it sends a signal to the maintenance department to perform corresponding equipment maintenance. When the abnormal alarm module receives a production abnormality signal, it sends a signal to the scheduling department to make corresponding adjustments to the production situation.

[0034] Compared with the prior art, the present invention provides a workshop production process radio frequency identification tracking management system, which has the following beneficial effects:

[0035] 1. The present invention realizes non-contact identification of objects through RFID tags, antennas, RFID readers and writers, and RFID back-end systems. There is no need to directly scan barcodes or manually input information, which greatly improves the speed and accuracy of data collection. Then, the product process data set is collected and monitored, and the location and status of the product can be tracked in real time to ensure the smooth progress of the production process.

[0036] 2. The present invention can avoid production line shutdown or suspension due to equipment failure through abnormal evaluation of production equipment. Effective abnormal evaluation can quickly take measures such as maintenance and replacement of parts to restore the equipment to normal operation as soon as possible, thereby ensuring the continuity and stability of production. By combining the production evaluation SCpg and various influencing factors to judge the actual production number, the progress of the current production can be clearly understood. When a deviation is found between the actual production volume and the planned progress, corresponding measures can be taken in time to make adjustments. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1 It is a schematic diagram of the structural system of the present invention; DETAILED DESCRIPTION

[0038] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0039] See also Figure 1 , a workshop production process radio frequency identification tracking and management system, including an RFID management system, a production data monitoring module, a production data analysis module and an abnormal alarm module;

[0040] The RFID management system includes RFID tags, antennas, RFID readers and RFID back-end systems. RFID tags are used to be attached to the surface of products to identify and record products. Antennas are used to transmit radio frequency signals between readers and tags. RFID readers are used to read tag information and send it to the RFID back-end system. The RFID back-end system is connected to the production data monitoring module through the network.

[0041] The production data monitoring module collects the location data of multiple products through the RFID backend system and forms production process data, collects the production data of products by connecting to the workshop production system, and collects the production influencing factor data by connecting to the network and the production machinery system. The production data monitoring module numbers multiple production process data to form a product process data set SXj, numbers multiple product production data to form a product production data set CSj, and numbers multiple production influencing factor data to form a production influencing factor data set YXj. The production data monitoring module sends the above data sets to the production data analysis module;

[0042] Through RFID tags, antennas, RFID readers and writers, and RFID back-end systems, non-contact identification of objects is achieved without directly scanning barcodes or manually entering information, which greatly improves the speed and accuracy of data collection. Then, the product process data set is collected and monitored to track the location and status of the product in real time to ensure the smooth progress of the production process. The product process data set includes multiple processes in the product production process. The expression of the product process data set is as follows:

[0043]

[0044] in, Represents the first process of production in the product process data set. Represents the last process produced in the product process data set. The subscript n represents that the current product has a total of n processes, and the superscript s represents the production time of the current process.

[0045] The production data set includes the production completion volume, production processing time, and production qualification rate. The expression of the product production data set is as follows:

[0046] CSj={WCsc、JGsj、SChg}

[0047] Among them, WCsc represents the production completion volume in the product production data set, JGsj represents the production processing time in the product production data set, and SChg represents the production qualification rate in the product production data set. The production completion volume can clearly understand the progress of production, find out the bottleneck link in the production process, and comprehensively evaluate the production process in combination with the production processing time and the production qualification rate;

[0048] The production influencing factor dataset includes the personnel impact rate, equipment failure rate, and production impact rate. The expression of the production influencing factor dataset is as follows:

[0049] YXj={RYyx、SBgz、SCyx}

[0050] Among them, RYyx represents the personnel impact rate in the production impact factor data set, SBgz represents the equipment failure rate in the production impact factor data set, and SCyx represents the production impact rate in the production impact factor data set. The above personnel impact rate, equipment failure rate, and production impact rate are all factors that seriously affect the production progress in the production process. Combining these factors can reduce the problem of production efficiency being affected by unexpected situations;

[0051] The production data analysis module calculates the production equipment abnormality evaluation SYpg, production evaluation SCpg and actual production number SJsc based on the product process data set SXj, product production data set CSj and production influencing factor data set YXj;

[0052] Production equipment abnormality assessment can avoid production line shutdown or production stoppage due to equipment failure. Effective abnormality assessment can quickly take measures such as maintenance and replacement of parts to restore the equipment to normal operation as soon as possible, thereby ensuring the continuity and stability of production. The calculation formula of production equipment abnormality assessment SYpg is as follows:

[0053]

[0054] In the above formula, Represents the total number of the vth aging of the i-th process and the aging after the vth aging of the i-th process in the product process data set, represents the total number of the vth aging of the i-th process in the product process data set and the aging before the vth aging of the i-th process, 2s means the difference is calculated twice, and PJrc is the tolerance value of the aging difference of all processes in the product process data set;

[0055] The calculation formula for production assessment SCpg is as follows:

[0056]

[0057] In the above formula, Z represents the total orders produced;

[0058] By combining the production evaluation SCpg and various influencing factors to judge the actual production number, we can clearly understand the progress of the current production. When the actual production volume deviates from the planned progress, we can take corresponding measures to adjust it in time. sc The calculation formula is as follows:

[0059] SJsc=(RYyx*τ+SBgz*σ+SCyx*ρ)*SCpg

[0060] In the above formula, τ represents the weight of the personnel impact rate in the production influencing factor data set, and σ represents the weight of the equipment failure rate in the production influencing factor data set. ρ Represents the weight of the production impact rate in the production impact factor data set;

[0061] The production data analysis module is internally provided with a production equipment abnormality threshold. When the production equipment abnormality evaluation SYpg is greater than the production equipment abnormality threshold, it is judged that the corresponding equipment of the current process is abnormal, and the equipment abnormality signal is sent to the abnormal alarm module;

[0062] The production data analysis module has an actual production threshold set inside. sc When the value is less than the actual production threshold, it is judged that the current production efficiency is abnormal, and a production abnormality signal is sent to the abnormal alarm module;

[0063] When the abnormal alarm module receives an equipment abnormality signal, it sends a signal to the maintenance department to perform corresponding equipment maintenance. When the abnormal alarm module receives a production abnormality signal, it sends a signal to the scheduling department to make corresponding adjustments to the production situation.

[0064] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A workshop production process radio frequency identification tracking and management system, characterized by: It includes RFID management system, production data monitoring module, production data analysis module and abnormal alarm module; The RFID management system includes an RFID tag, an antenna, an RFID reader and an RFID back-end system. The RFID tag is used to be attached to the surface of the product to identify and record the product. The antenna is used to transmit radio frequency signals between the reader and the tag. The RFID reader is used to read the tag information and send it to the RFID back-end system. The RFID back-end system is connected to the production data monitoring module through the network. The production data monitoring module collects the location data of multiple products through the RFID backend system and forms production process data, collects the production data of products by connecting to the workshop production system, and collects the production influencing factor data by connecting to the network and the production machinery system. The production data monitoring module numbers multiple production process data to form a product process data set SXj, numbers multiple product production data to form a product production data set CSj, and numbers multiple production influencing factor data to form a production influencing factor data set YXj. The production data monitoring module sends the above data sets to the production data analysis module; The production data analysis module calculates the production equipment abnormality evaluation SYpg, the production evaluation SCpg and the actual production number SJsc according to the product process data set SXj, the product production data set CSj and the production influencing factor data set YXj; The production data analysis module compares the production equipment abnormality assessment SYpg, the actual production number SJsc with the corresponding threshold value to determine whether there is an abnormality, and sends a signal to the abnormal alarm module if a problem occurs; The abnormal alarm module performs corresponding early warning processing according to the corresponding signal.

2. The workshop production process radio frequency identification tracking management system according to claim 1 is characterized by: The product process data set includes multiple processes in the product production process. The expression of the product process data set is as follows: in, Represents the first process of production in the product process data set. Represents the last process produced in the product process data set. The subscript n represents that there are n processes in total for the current product, and the superscript s represents the production time of the current process.

3. The workshop production process radio frequency identification tracking management system according to claim 1 is characterized by: The product production data set includes production completion volume, production processing time, and production qualification rate. The expression of the product production data set is as follows: CSj={WCsc、JGsj、SChg} Among them, WCsc represents the production completion volume in the product production data set, JGsj represents the production processing time in the product production data set, and SChg represents the production qualification rate in the product production data set.

4. The radio frequency identification tracking and management system for workshop production process according to claim 1, characterized in that: The production influencing factor data set includes a personnel impact rate, an equipment failure rate, and a production impact rate. The production influencing factor data set is expressed as follows: YXj={RYyx、SBgz、SCyx} Among them, RYyx represents the personnel impact rate in the production influencing factor data set, SBgz represents the equipment failure rate in the production influencing factor data set, and SCyx represents the production impact rate in the production influencing factor data set.

5. The workshop production process radio frequency identification tracking management system according to claim 2 is characterized by: The calculation formula of the production equipment abnormality assessment SYpg is as follows: In the above formula, Represents the total number of the vth aging of the i-th process and the aging after the vth aging of the i-th process in the product process data set, It represents the total number of aging times before the vth aging time of the i-th process in the product process data set and the bth aging time of the i-th process, 2s means the difference is calculated twice, and PJrc is the tolerance value of the aging difference of all processes in the product process data set.

6. The workshop production process radio frequency identification tracking management system according to claim 3 is characterized by: The calculation formula for the production evaluation SCpg is as follows: In the above formula, Z represents the total orders produced.

7. The workshop production process radio frequency identification tracking and management system according to claim 4 is characterized by: The calculation formula of the actual production number SJsc is as follows SJsc=(PYyx*τ+SBgz*σ+SCyx*ρ)*SCpg In the above formula, τ represents the weight of the personnel impact rate in the production influencing factor data set, σ represents the weight of the equipment failure rate in the production influencing factor data set, and ρ represents the weight of the production impact rate in the production influencing factor data set.

8. The radio frequency identification tracking and management system for workshop production process according to claim 5, characterized in that: The production data analysis module is internally provided with a production equipment abnormality threshold. When the production equipment abnormality assessment SYpg is greater than the production equipment abnormality threshold, it is determined that the corresponding equipment of the current process is abnormal, and an equipment abnormality signal is sent to the abnormal alarm module.

9. The workshop production process radio frequency identification tracking management system according to claim 7, characterized in that: The production data analysis module is internally provided with an actual production threshold. When the actual production number SJsc is less than the actual production threshold, it is determined that the current production efficiency is abnormal, and a production abnormality signal is sent to the abnormal alarm module.

10. The workshop production process radio frequency identification tracking management system according to claim 9, characterized in that: When the abnormal alarm module receives an equipment abnormality signal, it sends a signal to the maintenance department to perform corresponding equipment maintenance. When the abnormal alarm module receives a production abnormality signal, it sends a signal to the scheduling department to make corresponding adjustments to the production situation.

Images