TWI830189B - Anomaly detection device - Google Patents
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- 238000001514 detection method Methods 0.000 title claims abstract description 43
- 239000000463 material Substances 0.000 claims abstract description 85
- 238000005096 rolling process Methods 0.000 claims abstract description 74
- 238000000034 method Methods 0.000 claims description 133
- 230000008569 process Effects 0.000 claims description 91
- 230000005856 abnormality Effects 0.000 claims description 88
- 238000000605 extraction Methods 0.000 claims description 15
- 239000000284 extract Substances 0.000 abstract description 6
- 238000004519 manufacturing process Methods 0.000 description 75
- 238000005097 cold rolling Methods 0.000 description 29
- 238000005098 hot rolling Methods 0.000 description 27
- 238000003490 calendering Methods 0.000 description 20
- 230000008859 change Effects 0.000 description 15
- 230000002159 abnormal effect Effects 0.000 description 12
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- 239000010959 steel Substances 0.000 description 9
- 239000000047 product Substances 0.000 description 8
- 238000010586 diagram Methods 0.000 description 7
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- 238000004886 process control Methods 0.000 description 5
- 230000006866 deterioration Effects 0.000 description 4
- 238000002405 diagnostic procedure Methods 0.000 description 4
- 238000010438 heat treatment Methods 0.000 description 4
- 238000007726 management method Methods 0.000 description 4
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- 230000015556 catabolic process Effects 0.000 description 3
- 230000001364 causal effect Effects 0.000 description 3
- 230000003247 decreasing effect Effects 0.000 description 3
- 238000006731 degradation reaction Methods 0.000 description 3
- 238000003745 diagnosis Methods 0.000 description 3
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- 241000270295 Serpentes Species 0.000 description 1
- 238000013528 artificial neural network Methods 0.000 description 1
- 239000010960 cold rolled steel Substances 0.000 description 1
- 239000002826 coolant Substances 0.000 description 1
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B21—MECHANICAL METAL-WORKING WITHOUT ESSENTIALLY REMOVING MATERIAL; PUNCHING METAL
- B21B—ROLLING OF METAL
- B21B38/00—Methods or devices for measuring, detecting or monitoring specially adapted for metal-rolling mills, e.g. position detection, inspection of the product
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B21—MECHANICAL METAL-WORKING WITHOUT ESSENTIALLY REMOVING MATERIAL; PUNCHING METAL
- B21C—MANUFACTURE OF METAL SHEETS, WIRE, RODS, TUBES OR PROFILES, OTHERWISE THAN BY ROLLING; AUXILIARY OPERATIONS USED IN CONNECTION WITH METAL-WORKING WITHOUT ESSENTIALLY REMOVING MATERIAL
- B21C51/00—Measuring, gauging, indicating, counting, or marking devices specially adapted for use in the production or manipulation of material in accordance with subclasses B21B - B21F
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- 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
- G05B23/00—Testing or monitoring of control systems or parts thereof
- G05B23/02—Electric testing or monitoring
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- Mechanical Engineering (AREA)
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- Automation & Control Theory (AREA)
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Abstract
Description
本發明係關於一種檢測壓延系統(system)之異常的異常檢測裝置。 The present invention relates to an abnormality detection device for detecting abnormalities in a calendering system.
例如,壓延系統等係被使用於壓延鋼鐵等的壓延製程(process)中,該壓延系統係具備熱壓延生產線(line)及冷壓延生產線,且將素材(壓延材料)在複數個生產線或工序中各別進行壓延。 For example, a rolling system is used in a rolling process (process) such as steel rolling. The rolling system has a hot rolling production line (line) and a cold rolling production line, and the raw materials (rolled materials) are processed in multiple production lines or processes. Calendering is performed separately.
又,壓延製程係由於設備的隨時間劣化而發生異常,有時會給壓延的素材之品質帶來影響。 In addition, abnormality occurs in the rolling process due to equipment deterioration over time, which sometimes affects the quality of the rolled material.
例如,當壓延輥之冷卻液平衡(coolant balance)因閥(valve)異常等而崩毀時,就會在已被壓延過的素材發生彎曲等的形狀異常、或偏心(off-centering)等的移動性異常。 For example, when the coolant balance of the calendering roller is broken due to valve abnormality, etc., shape abnormalities such as bending or off-centering will occur in the rolled material. Abnormal mobility.
又,操作員(operator)係監視作業時的素材之狀態或製程資料(process data),且為了將該素材精加工成適當的品質精度,而介入藉由事先由計算機所設定之壓延條件所為的控制,且手動操作來調整壓延條件。 In addition, the operator monitors the state of the material or process data during the operation, and intervenes in the rolling conditions set by the computer in advance in order to finish the material to appropriate quality accuracy. control, and manual operation to adjust calendering conditions.
在此情況下,即便能藉由操作員之技術熟練度(skill)或技能知識(know-how)保持住素材之品質精度,仍無法得知在壓延製程是否已發生異常。一般而言,為了預防很有可能帶給作業重大影響的設備異常,早期檢測出製程之異常乃為設備產業整體的課題。 In this case, even if the quality accuracy of the material can be maintained through the operator's skill or know-how, it is still impossible to know whether an abnormality has occurred in the rolling process. Generally speaking, in order to prevent equipment abnormalities that are likely to have a significant impact on operations, early detection of process abnormalities is an issue for the entire equipment industry.
又,在一般被廣為使用的統計製程管理之手法中,係根據壓延後的素材之精度、或壓延之安定性等的壓延製程後之結果來檢測異常,只要在壓延結果中有異常,就會被判斷為在亦包含設備異常的壓延製程中已發生異常。 In addition, in the generally widely used statistical process management method, abnormalities are detected based on the results of the rolling process such as the accuracy of the rolled material or the stability of the rolling. As long as there is an abnormality in the rolling results, It will be judged that an abnormality has occurred in the rolling process that also includes equipment abnormality.
又,關於壓延製程之異常診斷,有一種將模型庫(model base)作為基本的方法係已揭示於專利文獻1。將資料活用作為基本的方法,例如已揭示於專利文獻2。
Furthermore, regarding abnormality diagnosis in the rolling process, a method using a model base as a basic method is disclosed in
在專利文獻1所揭示的異常診斷方法中,係使用正常作業時所獲得之製造過程中的複數種變數之實績值,來製作成預測製造中的製品之狀態的複數個經數學式表達的子模型(sub-model),且使用情境推論表(scenario inference list)來推定異常原因。
In the abnormality diagnosis method disclosed in
在此,有關構成製造過程的各個設備,係將製造前之素材實績相關、設備之設定相關、設備之實績相關、手動作業介入之實績相關、中間製品之狀態實績相關、及製造後之製品實績相關製作成以數學式表達的子模型。又,事先將在推定製造過程中已發生的異常狀態之原因時所使用的規則(rule)進行規定而作為情境推論表。 Here, regarding each equipment constituting the manufacturing process, we include material performance before manufacturing, equipment settings, equipment performance, manual work intervention performance, intermediate product status performance, and product performance after manufacturing. The correlation is made into a sub-model expressed in a mathematical expression. In addition, rules to be used when estimating the cause of an abnormal state that has occurred during the manufacturing process are defined in advance as a situation inference table.
然後,依每個子模型而檢測異常之有無,且使用情境推論表來推定製造後製品中的異常之原因。 Then, the presence or absence of an abnormality is detected for each sub-model, and the cause of the abnormality in the manufactured product is estimated using the situational inference table.
例如,在設備i中的製造過程之異常狀態的主因子(上游側因子)為「設備實績」,設備k中的製造過程之異常狀態的副因子(下游側因 子)為「人工介入實績」的情況下,係將「在設備i中發生設備異常,操作員為了補足設備異常而操作設備k,但是已發生失誤」的情形推定為製造過程之異常狀態的原因。 For example, the main factor (upstream factor) of the abnormal state of the manufacturing process in equipment i is "equipment performance", and the secondary factor (downstream factor) of the abnormal state of the manufacturing process in equipment k When sub) is "manual intervention performance", the situation of "an equipment abnormality occurred in equipment i, and the operator operated equipment k to compensate for the equipment abnormality, but an error occurred" is presumed to be the cause of the abnormal state in the manufacturing process .
但是,在製造實績中已發生異常時,該診斷方法會搜尋已造成異常之原因的設備、設定、人工介入來作為其因果關係。亦即,在該診斷方法中,係不包含以下的情形:不論在製造實績中是否有異常,都會檢測在包含設備的壓延製程中是否有異常。 However, when an abnormality occurs in manufacturing performance, this diagnostic method searches for the equipment, settings, and human intervention that caused the abnormality as the causal relationship. That is, this diagnostic method does not include the case where whether there is an abnormality in the rolling process including the equipment is detected regardless of whether there is an abnormality in the manufacturing results.
又,在專利文獻2係已揭示一種異常診斷方法,其可以對壓延設備等之中的設備及製品製程異常狀態之診斷方法及裝置,特別地明確異常原因與異常狀態之因果關係。
In addition,
又,在專利文獻2係已揭示一種說明變數廢棄方法,其係在進行線性多變量分析來診斷製品製程異常狀態的方法、以及使用神經網路(neural network)或基因演算法(genetic algorithm)來鑑定異常原因與異常狀態之因果關係的方法等之中,將成為外部干擾之不必要的說明變數廢棄的方法。
In addition,
但是,此等的診斷方法亦為針對作為壓延之結果所發現的異常,而用以在包含設備異常的壓延製程之異常中求出其原因的診斷方法。 However, these diagnostic methods are also diagnostic methods for finding the cause of the abnormality in the rolling process including equipment abnormality with respect to the abnormality discovered as a result of rolling.
[先前技術文獻] [Prior technical literature]
[專利文獻] [Patent Document]
專利文獻1:日本特許第6662222號公報 Patent Document 1: Japanese Patent No. 6662222
專利文獻2:日本特許第3892614號公報 Patent Document 2: Japanese Patent No. 3892614
如上述,以往已有提出一種方法,其在製品品質、壓延安定性等之壓延結果中已發生異常時,發現被考慮為原因的設備等之壓延製程異常。然而,在藉由操作員利用手動操作介入控制並補齊壓延製程異常而正常地保持住壓延結果的情況下,係無法檢測壓延製程之異常。 As mentioned above, a method has been proposed in the past. When an abnormality occurs in the rolling results such as product quality, rolling stability, etc., an abnormality in the rolling process of the equipment or the like that is considered to be the cause is discovered. However, in the case where the calendering results are normally maintained by the operator using manual operations to intervene in the control and correct the anomalies in the calendering process, the anomalies in the calendering process cannot be detected.
在實際的製造過程中,多是操作員等介入來調整壓延製程以便獲得所期望之壓延結果。 In the actual manufacturing process, operators often intervene to adjust the rolling process in order to obtain the desired rolling results.
本發明係為了解決如上述之課題而開發完成,其目的在於提供一種異常檢測裝置,即便處理素材的預定之工序後的素材滿足預定之規格,仍可以檢測在預定之工序中已發生的異常。 The present invention was developed to solve the above-mentioned problems, and its object is to provide an abnormality detection device that can detect an abnormality that has occurred in a predetermined process even if the material after the predetermined process of processing the material meets predetermined specifications.
本發明之一態樣的異常檢測裝置係檢測藉由預定之工序而壓延素材的壓延系統之異常,該異常檢測裝置係具有:工序前規格判定部,係判定前述預定之工序前的素材是否滿足預定之規格;工序後規格判定部,係判定前述預定之工序後的素材是否滿足預定之規格;介入操作量抽出部,係抽出操作員已對前述預定之工序介入之操作量;判定部,係至少在前述工序後規格判定部判定為滿足預定之規格,且前述介入操作量抽出部所抽出的操作量超過事先所決定之操作量的情況下,判定為在前述預定之工序已發生異常;以及輸出部,係輸出前述判定部所判定的結果。 An abnormality detection device according to one aspect of the present invention detects an abnormality in a rolling system that rolls materials through a predetermined process. The abnormality detection device includes a pre-process specification determination unit that determines whether the material before the predetermined process satisfies the predetermined process. The predetermined specifications; the post-process specification determination unit determines whether the materials after the aforementioned predetermined process meet the predetermined specifications; the intervention operation quantity extraction unit extracts the operation quantities that the operator has intervened in the aforementioned predetermined process; the determination unit is At least when the aforementioned post-process specification determination unit determines that the predetermined specifications are met and the operation amount extracted by the intervention operation amount extraction unit exceeds the predetermined operation amount, it is determined that an abnormality has occurred in the aforementioned predetermined process; and The output unit outputs the result determined by the determination unit.
又,本發明之一態樣的異常檢測裝置較佳為:前述判定部係藉由素材之規格、或依每個操作員而不同的基準來判定是否已發生異常。 Furthermore, in the abnormality detection device according to one aspect of the present invention, it is preferable that the determination unit determines whether an abnormality has occurred based on the specifications of the material or a criterion that differs for each operator.
又,本發明之一態樣的異常檢測裝置較佳為:前述判定部係使用非統計手法來判定是否已發生異常。 Furthermore, in the abnormality detection device according to one aspect of the present invention, it is preferable that the determination unit determines whether an abnormality has occurred using a non-statistical method.
依據本發明,即便處理素材的預定之工序後的素材滿足預定之規格,仍可以檢測在預定之工序中已發生的異常。 According to the present invention, even if the material after the predetermined process of processing the material meets the predetermined specifications, an abnormality that has occurred in the predetermined process can still be detected.
1:製程控制系統 1: Process control system
2:熱壓延生產線(壓延系統) 2: Hot calendering production line (calendering system)
3:冷壓延生產線(壓延系統) 3: Cold rolling production line (calendering system)
4:異常檢測裝置 4: Abnormal detection device
10:控制網路 10:Control network
20:加熱爐 20:Heating furnace
21:粗壓延機 21: Rough calender
22:截剪機 22:Cut machine
23:精壓延機 23:Precision calendering machine
24:冷卻裝置 24: Cooling device
25:捲取機 25: Coiler
26-1~26-4:感測器 26-1~26-4: Sensor
27:第一操作盤 27: First operation panel
28:第一控制裝置 28:First control device
30:開捲機 30: Uncoiler
31:入口側剪機 31: Entrance side shear machine
32:熔接機 32: Welding machine
33:活套 33:Looper
34:壓延機 34:Calender
35:出口側剪機 35:Export side shearing machine
36:張力捲筒 36: Tension drum
37:感測器 37: Sensor
38:第二操作盤 38: Second operating panel
39:第二控制裝置 39: Second control device
40:生產資訊記憶部 40:Production Information Memory Department
41:實績記憶部 41:Performance Memory Department
42:操作量記憶部 42: Operation quantity memory department
43:一致判定部 43: Unanimous Judgment Department
44:工序前規格判定部 44: Pre-process specification judgment department
45:工序後規格判定部 45: Post-process specification judgment department
46:介入操作量抽出部 46: Intervention operation volume extraction part
47:判定部 47: Judgment Department
48:輸出部 48:Output Department
圖1係顯示具備有壓延系統、以及檢測壓延系統之異常的異常檢測裝置的製程控制系統之構成例的圖。 FIG. 1 is a diagram showing a configuration example of a process control system including a rolling system and an abnormality detection device that detects abnormalities in the rolling system.
圖2係顯示有關一實施型態的異常檢測裝置之構成例的圖。 FIG. 2 is a diagram showing a configuration example of an abnormality detection device according to an embodiment.
圖3係顯示有關一實施型態的異常檢測裝置之動作例的流程圖(flowchart)。 FIG. 3 is a flowchart showing an operation example of the abnormality detection device according to one embodiment.
圖4係列舉異常檢測裝置檢測異常的工序、影響的設備劣化、及操作員手動介入的操作之具體例而顯示的圖。 FIG. 4 is a series of diagrams showing specific examples of processes in which an abnormality is detected by an abnormality detection device, equipment degradation affected, and manual intervention by an operator.
圖5係列舉異常檢測裝置檢測異常的工序、影響的設備劣化、及操作員手動介入的操作之具體例而顯示的圖。 5 is a series of diagrams showing specific examples of processes in which an abnormality is detected by an abnormality detection device, equipment degradation affected, and manual intervention by an operator.
以下,使用圖式來說明檢測壓延系統之異常的異常檢測裝置之一實施型態。圖1係顯示具備有壓延系統、以及檢測壓延系統之異常的異常檢測裝置的製程控制系統1之構成例的圖。
Hereinafter, one embodiment of the abnormality detection device for detecting abnormality in the rolling system will be described using drawings. FIG. 1 is a diagram showing a configuration example of a
如圖1所示,製程控制系統1係藉由例如作為二個壓延系統的熱壓延生產線2及冷壓延生產線3各別透過控制網路10而被連接於異常檢測裝置4所構成,且藉由複數個壓延工序而依序地壓延素材(壓延材料)。
As shown in FIG. 1 , the
控制網路10,例如是LAN(Local Area Network;區域網路)等的網路,亦能夠以包含控制用LAN及資訊系統LAN的方式所構成。
The
熱壓延生產線2,例如是具有加熱爐(RF:Reheating Furnace)20、粗壓延機(RM:Roughing mill)21、截剪機(CS:Crop Shear)22、精壓延機(FM:Finishing mill)23、冷卻裝置(ROT:Run Out Table)24、及捲取機(DC:Down Coiler)25。又,熱壓延生產線2,例如是以具備感測器(sensor)26-1至26-4,且藉由操作員操作第一操作盤27而由第一控制裝置28控制構成熱壓延生產線2的各部之方式所構成。
The hot
熱壓延生產線2係粗壓延機21對加熱爐20輸出的扁鋼胚(slab)進行粗壓延,且將截剪機22切斷後的壓延材料饋送至精壓延機23。然後,熱壓延生產線2係由精壓延機23將被粗壓延過的壓延材料更進一步壓延至預定之規格,且在冷卻裝置24使其冷卻之後由捲取機25進行捲取。如此,熱壓延生產線2係包含複數個工序來對壓延材料進行預定之處理。
The hot
又,感測器26-1,例如是被配置於粗壓延機21之出口側,檢測藉由粗壓延機21所壓延過的壓延材料之壓延實績資料,且輸出至第一控
制裝置28。例如,感測器26-1係檢測壓延工序中的各個實績值,以便第一控制裝置28可以取得在壓延方向(壓延材料之行進方向)不同的複數個位置之各個位置中的壓延材料之長度、厚度、寬度及溫度等。
In addition, the sensor 26-1 is, for example, disposed on the outlet side of the rough calender 21, detects the rolling performance data of the rolled material rolled by the rough calender 21, and outputs it to the first control unit.
感測器26-2係被配置於精壓延機23之入口側,檢測被饋送至精壓延機23的壓延材料之壓延實績資料,且輸出至第一控制裝置28。例如,感測器26-2係檢測與壓延材料相對的各個實績值,以便第一控制裝置28可以取得在壓延方向不同的複數個位置之各個位置中的壓延材料之長度、厚度、寬度及溫度等。
The sensor 26 - 2 is arranged on the entrance side of the finishing
感測器26-3係被配置於精壓延機23之出口側,檢測藉由精壓延機23所壓延過的壓延材料之壓延實績資料,且輸出至第一控制裝置28。例如,感測器26-3係檢測壓延工序中的各個實績值,以便第一控制裝置28可以取得在壓延方向不同的複數個位置之各個位置中的壓延材料之長度、厚度、寬度及溫度等。
The sensor 26 - 3 is arranged on the outlet side of the finishing
感測器26-4係被配置於冷卻裝置24之出口側,檢測藉由冷卻裝置24所冷卻後的壓延材料之壓延實績資料,且輸出至第一控制裝置28。例如,感測器26-4係檢測冷卻工序後的各個實績值,以便第一控制裝置28可以取得在壓延方向不同的複數個位置之各個位置中的壓延材料之長度、厚度、寬度及溫度等。
The sensor 26 - 4 is arranged on the outlet side of the
然後,第一控制裝置28係將感測器26-1至26-4檢測出的各個壓延實績資料透過控制網路10而發送至異常檢測裝置4。又,熱壓延生產線2係設置有多個未圖示之其他的感測器,且將感測器檢測出的各種資料各別發送至異常檢測裝置4。
Then, the
冷壓延生產線3,例如是具有開捲機(pay-off reel)30、入口側剪機31、熔接機32、活套(looper)33、壓延機34、出口側剪機35、張力捲筒(tension reel)36、複數個感測器37、第二操作盤38及第二控制裝置39。然後,冷壓延生產線3係以藉由操作員操作第二操作盤38,而由第二控制裝置39控制構成冷壓延生產線3的各部之方式所構成。
The cold
冷壓延生產線3係將熱壓延生產線2之捲取機25捲取後的壓延材料的鋼捲(coil)之尾端作為前端,並將熱壓延生產線2所壓延過的壓延材料做更進一步壓延。
The cold
更具體而言,開捲機30係將捲取機25捲取後的鋼捲之尾端作為前端,將壓延材料朝向入口側剪機31導出。入口側剪機31及出口側剪機35係為了調整壓延材料之前端及尾端,而藉由前後的夾送輥(pinch roll)(未圖示)來包夾壓延材料並使其通過,且因應第二控制裝置39之控制而切斷壓延材料。
More specifically, the uncoiler 30 uses the tail end of the steel coil coiled by the coiler 25 as the front end to lead the rolled material toward the
熔接機32係具有以熔接來連接鋼捲與鋼捲而使對複數個鋼捲進行的壓延工序可連續性地進行的功能。活套33係留存壓延材料,且對壓延機34固定供給壓延材料。
The
壓延機34係將壓延材料做更進一步壓延。張力捲筒36係捲取壓延機34所壓延過的壓延材料。如此,冷壓延生產線3係包含複數個工序而對壓延材料進行預定之處理。
The
複數個感測器37係配置於被設置於壓延機34內的複數個支架(stand)周邊,例如檢測壓延材料之厚度等,且輸出至第二控制裝置39。又,感測器37亦可檢測壓延工序中的各個實績質,以便第二控制裝置39
可以取得在壓延方向不同的複數個位置之各個位置中的壓延材料之長度、寬度及溫度等。
A plurality of sensors 37 are arranged around a plurality of stands provided in the
然後,第二控制裝置39係將各個感測器37等檢測出的各個壓延實績資料透過控制網路10而發送至異常檢測裝置4。又,冷壓延生產線3係設置有多個未圖示之其他的感測器,且將感測器檢測出的各種資料各別發送至異常檢測裝置4。
Then, the
如此,製程控制系統1係藉由熱壓延生產線2及冷壓延生產線3來各別將壓延材料進行壓延,且由異常檢測裝置4接收各個壓延工序中的實績時間序列資料等。又,異常檢測裝置4係接收表示操作員已對第一操作盤27及第二操作盤38進行之操作的資訊。換句話說,異常檢測裝置4係收集操作員已對熱壓延生產線2及冷壓延生產線3操作的操作量。
In this way, the
其次,針對異常檢測裝置4之構成例加以詳述。圖2係顯示有關一實施型態的異常檢測裝置4之構成例的圖。異常檢測裝置4,例如是具備有CPU的電腦(computer)等,且具有生產資訊記憶部40、實績記憶部41、操作量記憶部42、一致判定部43、工序前規格判定部44、工序後規格判定部45、介入操作量抽出部46、判定部47及輸出部48。
Next, a structural example of the
生產資訊記憶部40係事先記憶熱壓延生產線2及冷壓延生產線3中的壓延材料之生產資訊(生產條件等)。生產資訊,例如是包含被投入於熱壓延生產線2及冷壓延生產線3的素材之鋼種、製品尺寸等之事先所設定的計算機資料。
The production
實績記憶部41係記憶熱壓延生產線2及冷壓延生產線3所發送的實績時間序列資料。實績時間序列資料為各個感測器檢測出熱壓延
生產線2及冷壓延生產線3在各個工序中處理後之壓延材料的結果等。例如,實績時間序列資料為與壓延材料之品質精度、壓延現象之安定度、精度以外之品質間題等相關的資料。
The
操作量記憶部42係記憶表示操作員已以自身的判斷對第一操作盤27及第二操作盤38手動進行之操作(槓桿(lever)操作或增益(gain)調整等)的資訊(時間序列資料)。換句話說,異常檢測裝置4係能夠收集操作員已對熱壓延生產線2及冷壓延生產線3操作的各個操作量。
The operation
一致判定部43係取得表示操作員已透過第一操作盤27或第二操作盤38輸入之對熱壓延生產線2或冷壓延生產線3進行製程開始操作的資訊,且讀取生產資訊記憶部40所記憶的生產資訊。又,一致判定部43係判定熱壓延生產線2或冷壓延生產線3在各個工序執行的製程與讀取出的生產資訊之一致。
The
其次,一致判定部43係從生產資訊記憶部40所記憶的複數個生產條件之中具體指定熱壓延生產線2或冷壓延生產線3在各個工序執行的製程。然後,一致判定部43係將預定之工序前所應有的基準規格輸出至工序前規格判定部44。又,一致判定部43係將預定之工序後所應有的基準規格輸出至工序後規格判定部45。又,一致判定部43係將操作員在預定之工序中通常能介入的操作量(基準操作量:例如臨限值等)輸出至判定部47。
Next, the
工序前規格判定部44係比較從一致判定部43所輸入的預定之工序前的基準規格、與從實績記憶部41讀取出的預定之工序前的實績時間序列資料,且判定預定之工序前的壓延材料是否滿足預定之規格。換句
話說,工序前規格判定部44係將預定之工序前的壓延材料之精度定量化並監視變化。然後,工序前規格判定部44係將判定結果輸出至判定部47。
The pre-process
工序後規格判定部45係比較從一致判定部43所輸入的預定之工序後的基準規格、與從實績記憶部41讀取出的預定之工序後的實績時間序列資料,且判定預定之工序後的壓延材料是否滿足預定之規格。換句話說,工序後規格判定部45係將預定之工序後的壓延材料之精度定量化並監視變化。然後,工序後規格判定部45係將判定結果輸出至判定部47。
The post-process
介入操作量抽出部46係從操作量記憶部42讀取表示操作員已以自身的判斷對第一操作盤27及第二操作盤38手動進行之操作的資訊(時間序列資料),並各別抽出表示操作員已對熱壓延生產線2及冷壓延生產線3中的各個預定之工序手動介入之操作量的介入操作量,且輸出至判定部47。換句話說,介入操作量抽出部46係抽出操作員之操作量,且定量化並監視變化。
The intervention operation
判定部47係至少在工序後規格判定部45判定為滿足預定之規格,且介入操作量抽出部46所抽出的操作量(介入操作量)超過事先所決定之操作量(基準操作量:例如臨限值)的情況下,判定為在該預定之工序已發生異常。然後,判定部47係將所判定的結果輸出至輸出部48。
The
再者,判定部47例如亦可藉由透過第一操作盤27或第二操作盤38所輸入的壓延材料之規格、或依每個操作員而不同的基準(例如特定條件),來判定是否已發生異常。此是因考慮到介入的操作量會依每個壓延材料之規格、或依每個操作員而不同所致。又,判定部47亦可使用聚類(clustering)等非統計手法來判定是否已發生異常。
Furthermore, the
如此,判定部47係基於操作員之操作量來判定操作員之操作是否有助於壓延材料之精度維持,並以邏輯(logic)與臨限值等來判定操作員之操作量與預定之工序後的壓延材料精度之相互關係。
In this way, the
輸出部48係輸出從判定部47所輸入的判定結果。例如,輸出部48,既可藉由將從判定部47所輸入的判定結果或製程變化顯示於顯示器(display)等來輸出,又可藉由聲音或光等來輸出。
The
換句話說,異常檢測裝置4係在即便生產條件為相同且製程後的素材精度(壓延材料精度)滿足預定之規格,但該製程中的操作員之操作量仍從成為基準的過去資料等乖離的情況下,判定為製程之異常。
In other words, the
圖3係顯示有關一實施型態的異常檢測裝置4之動作例的流程圖。如圖3所示,異常檢測裝置4在步驟100(S100)中,係由一致判定部43從生產資訊記憶部40所記憶的複數個生產條件之中具體指定熱壓延生產線2或冷壓延生產線3在各個工序執行的製程。
FIG. 3 is a flowchart showing an operation example of the
在步驟102(S102)中,工序前規格判定部44係比較從一致判定部43所輸入的預定之工序前的基準規格、與從實績記憶部41讀取出的預定之工序前的實績時間序列資料,且判定預定之工序前的壓延材料是否滿足預定之規格。
In step 102 (S102), the pre-process
在步驟104(S104)中,工序後規格判定部45係比較從一致判定部43所輸入的預定之工序後的基準規格、與從實績記憶部41讀取出的預定之工序後的實績時間序列資料,且判定預定之工序後的壓延材料是否滿足預定之規格。
In step 104 (S104), the post-process
在步驟106(S106)中,介入操作量抽出部46係從操作量記憶部42讀取表示操作員已以自身的判斷對第一操作盤27及第二操作盤38手動進行之操作的資訊(時間序列資料),並各別抽出表示操作員已對熱壓延生產線2及冷壓延生產線3中的各個預定之工序手動介入之操作量的介入操作量。
In step 106 (S106), the intervention operation
在步驟108(S108)中,判定部47係至少在工序後規格判定部45判定為滿足預定之規格,且介入操作量抽出部46所抽出的操作量(介入操作量)超過事先所決定之操作量(基準操作量:例如臨限值)的情況下,判定為在該預定之工序已發生異常。
In step 108 (S108), the
在步驟110(S110)中,輸出部48係輸出從判定部47所輸入的判定結果。
In step 110 (S110), the
其次,以在熱壓延生產線2的素材之壓延時的彎曲為例,來說明異常檢測裝置4之動作的具體例。
Next, a specific example of the operation of the
首先,一致判定部43係將生產資訊(鋼種、製品尺寸等)作為來自未圖示之計算機的輸入資料,並使用素材之鋼種編號、板厚區分編號及板寬區分編號等來決定對該素材的層別編號。此時,全部之素材係被決定層別編號,且同一層別編號被視為同一生產條件。
First, the
工序前規格判定部44係將工序前的素材之實績時間序列資料(品質精度、壓延現象之不安定、精度以外之品質問題等)作為輸入資料,並將粗壓延出口側的素材之彎曲量定量化,且監視粗壓延出口側的素材之彎曲量的變化。工序前規格判定部44係使用將已超過例如藉由X-s管理圖所得的1σ之臨限值的資料判定為異常的方法,來作為監視方法。
The pre-process
工序後規格判定部45係將工序後的素材之實績時間序列資料(品質精度、壓延現象之不安定、精度以外之品質問題等)作為輸入資料,並將精壓延出口側的素材之彎曲量定量化,且監視精壓延出口側的素材之彎曲量的變化。工序後規格判定部45係使用將已超過例如藉由X-s管理圖所得的1σ之臨限值的資料判定為異常的方法,來作為監視方法。
The post-process
介入操作量抽出部46係將操作員之操作量(槓桿、增益等)之時間序料資料作為輸入資料,並將藉由操作員對精壓延工序所為的間隙調平(gap leveling)之操作量予以抽出及定量化,且監視操作量之變化。介入操作量抽出部46係使用將已超過例如藉由X-s管理圖所得的2σ之臨限值的資料判定為異常的方法,來作為監視方法。
The intervention operation
判定部47,例如是如以下所示判定精壓延或粗壓延之製程變化及製程中的異常之有無。在製程變化中係有起因於輥(roll)的間隙之左右不平衡、及起因於壓下裝置的間隙之左右不平衡等。
The
然後,判定部47係使用邏輯與臨限值來判定操作員之操作量與工序後素材精度之相互關係,且檢測該製程之變化。
Then, the
例如,判定部47,亦可在粗壓延出口側的素材之彎曲量中沒有變化而為正常的精度,在精壓延出口側的素材之彎曲量中亦沒有變化而為正常的精度,且操作員之操作量變化大的情況下,判定為已由操作員操作(operation)而吸收製程變化。
For example, the
又,判定部47,亦可在粗壓延出口側的素材之彎曲量中有變化,在精壓延出口側的素材之彎曲量中沒有變化而為正常的精度,且操作
員之操作量變化大的情況下,判定為在該製程與前工序製程之雙方、或其中任一方的製程中發生變化,且已由操作員操作而吸收製程變化。
In addition, the
具體而言,判定部47,例如是在操作員之操作量超過2σ之臨限值,且工序後的素材之精度為1σ以內的情況下,對壓延其鋼捲後的精壓延工序判定為有製程異常之可能性。
Specifically, for example, when the operator's operation amount exceeds the threshold value of 2σ and the accuracy of the material after the process is within 1σ, the
判定部47所判定的結果係由輸出部48例如顯示於顯示器等。
The result determined by the
其次,針對異常檢測裝置4檢測異常的工序(被控制對象)、與操作員手動介入的操作(介入方法)之具體例加以說明。圖4、圖5係列舉異常檢測裝置4檢測異常的工序(被控制對象)、影響的設備劣化、及操作員手動介入的操作(介入方法)之具體例而顯示的圖。
Next, specific examples of the process (controlled object) in which the
在鋼帶整平機嚙合(strip leveler intermesh)〈冷壓延/製程〉中,操作員係於整平機推壓壓力已變化的情況下,進行增多嚙合之量的操作。 In the strip leveler intermesh (cold rolling/process), the operator performs an operation to increase the amount of meshing when the leveler pushing pressure has changed.
又,在冷壓延鋼板之形狀控制〈冷壓延〉中,操作員係於輥之粗度已變化的情況下,手動進行藉由斷開(off)形狀控制所為的彎曲機(bender)/調平機(leveling)之介入操作、或目標形狀變更。 Furthermore, in the shape control of cold-rolled steel plates (cold rolling), the operator manually performs bending/leveling by turning off the shape control when the thickness of the roll has changed. Intervention operation of machine (leveling) or target shape change.
又,在張力捲筒用盤繞完成判定〈冷壓延/製程〉中,操作員係於已發生心軸(mandrel)之磨耗係數劣化(粗度降低)的情況下,進行提高速度導程率(speed lead rate)、或使盤繞完成時序(timing)延遲的操作。 Furthermore, in the tension roll winding completion determination (cold rolling/process), the operator increases the speed lead rate (speed) when the wear coefficient of the mandrel (mandrel) has deteriorated (decreased roughness). lead rate), or operations that delay winding completion timing.
又,在張緊裝置(bridle)張力控制(沒有張力計(tension meter))〈冷壓延/製程〉中,操作員係於已發生張緊裝置/齒輪之GD2變 化(由於油脂(grease)劣化/不足所致的影響)的情況下,為了避免張緊裝置/齒輪鬆開,而進行提高張力設定並對馬達提供扭矩(torque)的操作。 Also, in the tension control of the tension device (without tension meter) (cold rolling/process), the operator is in the condition that the GD2 change of the tension device/gear has occurred. (effect due to grease deterioration/insufficiency), in order to avoid loosening of the tensioner/gear, increase the tension setting and provide torque to the motor.
又,在熱壓延CTC控制〈熱壓延〉中,操作員係於已發生噴閥(spray valve)之接通(on)/斷開(off)速度劣化的情況下,進行切換成固定庫(bank)設定、或使閥延遲速度(valve delay speed)設定配合實際狀態的操作。 In addition, in the hot rolling CTC control <hot rolling>, when the on/off speed of the spray valve (spray valve) has deteriorated, the operator switches to the fixed library. (bank) setting, or the valve delay speed (valve delay speed) setting to match the actual status of the operation.
又,在入口側/出口側鋼捲小車(coil car)位置控制〈冷壓延/製程〉中,操作員係於已發生油壓源降低、軌道(rail)之摩擦係數變化的情況下,因為變得無法在預定之位置停止,故而進行藉由寸動(inching)操作而做微調的操作。 Also, in the entry/exit side coil car position control (cold rolling/process), the operator is in a situation where the oil pressure source has decreased and the friction coefficient of the rail has changed, because It becomes impossible to stop at a predetermined position, so fine-tuning operations are performed by inching operations.
又,在藉由板厚計所為的板厚量測〈熱壓延/冷壓延〉中,操作員係於已發生板厚計線源降低、X線軸偏移的情況下,進行對目標板厚附加補償(offset)、或對AGC控制之板厚變動目標(通常為0)附加補償的操作。 In addition, in the plate thickness measurement (hot rolling/cold rolling) by the plate thickness gauge, the operator performs the target plate thickness measurement when the line source of the plate thickness meter has decreased and the X-line axis has shifted. Additional compensation (offset), or the operation of additional compensation to the plate thickness change target (usually 0) controlled by AGC.
又,在壓延機之速度控制〈熱壓延/冷壓延〉中,操作員係於已發生由於壓延機外殼(housing)、輥、齒輪、馬達之劣化所致的共振頻率之變化的情況下,進行實施已避開共振速度區之作業、或變更所產生的鋼板之排程(schedule)的操作。 Furthermore, in the speed control of the calender (hot calendering/cold calendering), when the resonant frequency has changed due to the deterioration of the calender housing, rollers, gears, and motors, the operator Perform operations that avoid the resonance speed zone or change the schedule of the steel plates to be produced.
又,在活套車(loop car)〈冷壓延/製程〉中,操作員係於已發生活套車外殼之傾斜、擺動(swing)機構之故障(蛇行、或板之震動變大)的情況下,進行將同步位置設定於短端側並以活套車不到達長端側的方式設定的操作。 Also, in the loop car (cold rolling/process), the operator was in a situation where the tilt and swing mechanism of the loop car shell had malfunctioned (snake, or the vibration of the plate became larger). Next, set the synchronization position to the short end side so that the looper does not reach the long end side.
又,在擠水輥(wiper roll)控制〈冷壓延/製程〉中,操作員係於已發生擠水輥(橡膠輥(rubber roll))之表面劣化的情況下,進行增大擠水輥之推壓量的操作。 Also, in the wiper roll control (cold calendering/process), the operator increases the wiper roll when the surface of the wiper roll (rubber roll) has deteriorated. Push volume operation.
又,在製程生產線(process line)中的爐內的板之直進性(蛇行)中,操作員係於爐之特性、或加熱裝置已劣化及變化的情況下,進行附加設定補償量以便實績成為所期望之張力的操作。 In addition, when the characteristics of the furnace or the heating device have deteriorated or changed in the linear motion (snaking) of the plate in the furnace in the process line, the operator additionally sets the compensation amount so that the actual performance becomes The desired tension operation.
又,在SPM(表皮輥軋機(skin pass mill))拉伸率中,操作員係於表皮輥軋機之剛性及壓下系統劣化及變化,並未到達L2(預定之等級2)所設定的目標荷重的情況下,進行對SPM荷重之目標值做設定變更的操作。 Furthermore, in the SPM (skin pass mill) stretch rate, the operator did not reach the target set by L2 (predetermined level 2) due to the deterioration and changes in the rigidity and reduction system of the skin pass mill. In the case of load, perform an operation to change the setting of the SPM load target value.
如以上說明,由於異常檢測裝置4係至少在工序後規格判定部45判定為滿足預定之規格,且介入操作量抽出部46所抽出的操作量超過事先所決定之操作量的情況下,判定為在該預定之工序已發生異常,所以即便處理素材的預定之工序後的素材滿足預定之規格,仍可以檢測在預定之工序中已發生的異常。
As described above, the
再者,異常檢測裝置4所具有的各個功能,其各自之一部分或全部既可藉由PLD(Programmable Logic Device;可程式邏輯元件)或FPGA(Field Programmable Gate Array;現場可程式閘陣列)等硬體(hardware)所構成,又可構成作為CPU等處理器(processor)所執行的程式(program)。
Furthermore, some or all of the various functions of the
4:異常檢測裝置 4: Abnormal detection device
40:生產資訊記憶部 40:Production Information Memory Department
41:實績記憶部 41:Performance Memory Department
42:操作量記憶部 42: Operation variable memory department
43:一致判定部 43: Unanimous Judgment Department
44:工序前規格判定部 44: Pre-process specification judgment department
45:工序後規格判定部 45: Post-process specification judgment department
46:介入操作量抽出部 46: Intervention operation volume extraction part
47:判定部 47:Judgment Department
48:輸出部 48:Output Department
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WOPCT/JP2021/026347 | 2021-07-13 |
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Citations (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JPH11347614A (en) * | 1998-06-05 | 1999-12-21 | Mitsubishi Electric Corp | Method and device for abnormality diagnosis |
JP2004167604A (en) * | 2002-11-20 | 2004-06-17 | Posco Corp Ltd | Apparatus and method for diagnosing finish rolling abnormality |
WO2018096682A1 (en) * | 2016-11-28 | 2018-05-31 | 東芝三菱電機産業システム株式会社 | Method and device for diagnosing abnormality in rolling equipment |
TW201928322A (en) * | 2017-09-22 | 2019-07-16 | 日商蒂業技凱股份有限公司 | Method for diagnosing state of rolling guide device |
JP2019181483A (en) * | 2018-04-03 | 2019-10-24 | Jfeスチール株式会社 | Rolling control method and rolling control device for hot finish rolling |
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- 2021-07-13 JP JP2022506813A patent/JP7156569B1/en active Active
- 2021-07-13 CN CN202180060937.6A patent/CN116324654A/en active Pending
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Patent Citations (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JPH11347614A (en) * | 1998-06-05 | 1999-12-21 | Mitsubishi Electric Corp | Method and device for abnormality diagnosis |
JP2004167604A (en) * | 2002-11-20 | 2004-06-17 | Posco Corp Ltd | Apparatus and method for diagnosing finish rolling abnormality |
WO2018096682A1 (en) * | 2016-11-28 | 2018-05-31 | 東芝三菱電機産業システム株式会社 | Method and device for diagnosing abnormality in rolling equipment |
TW201928322A (en) * | 2017-09-22 | 2019-07-16 | 日商蒂業技凱股份有限公司 | Method for diagnosing state of rolling guide device |
JP2019181483A (en) * | 2018-04-03 | 2019-10-24 | Jfeスチール株式会社 | Rolling control method and rolling control device for hot finish rolling |
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CN116324654A (en) | 2023-06-23 |
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