JPH0299834A - Detection of defective article in production line - Google Patents
Detection of defective article in production lineInfo
- Publication number
- JPH0299834A JPH0299834A JP25342088A JP25342088A JPH0299834A JP H0299834 A JPH0299834 A JP H0299834A JP 25342088 A JP25342088 A JP 25342088A JP 25342088 A JP25342088 A JP 25342088A JP H0299834 A JPH0299834 A JP H0299834A
- Authority
- JP
- Japan
- Prior art keywords
- weight
- products
- defective
- product
- control range
- 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.)
- Pending
Links
- 230000002950 deficient Effects 0.000 title claims abstract description 36
- 238000004519 manufacturing process Methods 0.000 title claims description 6
- 238000001514 detection method Methods 0.000 title description 3
- 238000000034 method Methods 0.000 claims abstract description 8
- 238000007689 inspection Methods 0.000 claims description 7
- 238000005259 measurement Methods 0.000 abstract description 6
- 230000002265 prevention Effects 0.000 abstract 1
- 239000002994 raw material Substances 0.000 description 5
- 238000010561 standard procedure Methods 0.000 description 5
- 230000000704 physical effect Effects 0.000 description 3
- 235000009508 confectionery Nutrition 0.000 description 2
- 230000000694 effects Effects 0.000 description 2
- 238000004806 packaging method and process Methods 0.000 description 2
- 238000007430 reference method Methods 0.000 description 2
- MIDXCONKKJTLDX-UHFFFAOYSA-N 3,5-dimethylcyclopentane-1,2-dione Chemical compound CC1CC(C)C(=O)C1=O MIDXCONKKJTLDX-UHFFFAOYSA-N 0.000 description 1
- 241000282320 Panthera leo Species 0.000 description 1
- 206010049040 Weight fluctuation Diseases 0.000 description 1
- 235000013736 caramel Nutrition 0.000 description 1
- 238000007796 conventional method Methods 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 230000005484 gravity Effects 0.000 description 1
- 238000012858 packaging process Methods 0.000 description 1
- 238000007619 statistical method Methods 0.000 description 1
Landscapes
- Sorting Of Articles (AREA)
Abstract
Description
【発明の詳細な説明】
[産業上の利用分野]
本発明は、生産ラインにおける不良品の検出方法に関す
るものである。DETAILED DESCRIPTION OF THE INVENTION [Industrial Field of Application] The present invention relates to a method for detecting defective products in a production line.
[従来の技術]
工場の生産ラインにおいて生産される一般消費者向けの
製品の多くは、1個毎あるいは複数個の集積体として包
装され、市場に供給される。そのため、通常は、包装工
程に、良品と不良品を区別して不良品を排除する検査機
構が設置されている。このような検査機構は、生産され
る製品の種類によって検査対象となる品質か異なるか、
殆ど全ての製品において重量の適不適か検査されている
。[Prior Art] Many products for general consumers produced on factory production lines are packaged individually or as a collection of multiple products and supplied to the market. Therefore, an inspection mechanism is usually installed in the packaging process to distinguish between good and defective products and eliminate defective products. This kind of inspection mechanism has different qualities to be inspected depending on the type of product being produced.
Almost all products are inspected for proper weight.
製品の重量を検査する重量検査機では、従来から、製品
の標準重量を基準値にとり、実測した重量のバラツキを
もとに、良品の許容範囲あるいは管理幅を設定するとい
う固定した基準値を用いる方法(以下、固定基準法と略
記する。)か採用されてきた。Weight inspection machines that inspect the weight of products have traditionally used a fixed reference value that takes the standard weight of the product as a reference value and sets an acceptable range or control range for non-defective products based on the variation in the measured weight. method (hereinafter abbreviated as fixed reference method) has been adopted.
しかし、この固定基準法は、基本的な考え方か、無限大
の母集団を想定して統計的手法により管理幅を設定する
ものであるため、そのまま適用すると、良品として許容
する範囲が極めて広くなり、製品中に多量の不良品か混
入する結果を生じるおそれかある。このような問題点を
回避するため、良品か排除される程度と不良品か混入す
る危険性とを考慮して、適当な管理幅を設定しているか
、製品重量にバラツキかある場合には十分な検査機能を
発揮できないという欠点がある。However, since this fixed standard method is based on a basic idea or sets a control range using statistical methods assuming an infinite population, if applied as is, the range of acceptable products will be extremely wide. This may result in a large amount of defective products being mixed into the product. In order to avoid such problems, we have set an appropriate control range, taking into account the degree to which good products are rejected and the risk of defective products being mixed in, or if there is variation in product weight, The disadvantage is that it cannot perform a thorough inspection function.
特に、製造工程に供給される原材料の物性のうち、製品
の重量に影響を与える物性か変動しやすい場合には、固
定基準法では管理幅を広くするか、頻繁に手作業で基準
値を設定し直さなければならないため、製品中に不良品
の混入する可能性が増大するか、あるいは余分に人手を
要し、かつ基準値のコントロールのタイミンクを間違え
ると、不良品を良品とするミスも生じやすい。In particular, when the physical properties of raw materials supplied to the manufacturing process that affect the weight of the product are likely to fluctuate, the fixed standard method requires a wide control range or frequently sets standard values manually. This increases the possibility that defective products will be mixed into the product, or requires additional manpower, and if the timing of the control of the reference value is incorrect, there may be mistakes in identifying defective products as non-defective products. Cheap.
[発明か解決しようとする課題]
本発明の技術的課題は、生産ラインにおいて重量の測定
により製品の重量不良品を検知するにあたり、良品の合
格範囲(管理幅)を狭くすることを可能にし、それによ
って製品中に不良品か混入するのを防止し、あるいはそ
の可能性を最少限に減らすことにある。[Problem to be solved by the invention] The technical problem of the present invention is to make it possible to narrow the acceptable range (control range) of non-defective products when detecting weight-defective products by measuring weight on a production line. The purpose of this is to prevent or minimize the possibility of defective products being mixed into the product.
[課題を解決するための手段、作用]
上記課題を解決するため、本発明の不良品検出方法にお
いては、生産される製品の重量を測定してその重量か管
理幅内にあるか否かを検査機構により検査し、良品と不
良品を区別して不良品を排除するに際し、上記管理幅を
設定する数値として、直前に重量を測定して良品と判定
された3〜20個の製品の重量から計算した平均値(以
下、移動平均値という。)を用い、それによって設定さ
れる管理幅により製品重量の良不良の判定を行うという
手段を用いている。[Means and effects for solving the problem] In order to solve the above problem, the defective product detection method of the present invention measures the weight of the product to be produced and determines whether or not the weight is within the control range. When inspected by the inspection mechanism to distinguish between good and defective products and eliminate defective products, the above control range is set based on the weight of 3 to 20 products that were determined to be non-defective by measuring the weight immediately before. The calculated average value (hereinafter referred to as moving average value) is used to determine whether the product weight is good or bad based on the control range set based on the calculated average value.
原材料の重量、比重、体積、容積、粘度等の測定によっ
て、その物性の変動が検知できる場合に、その物性の多
くは経時的に規則的に変動を生しることが少なくない。When changes in physical properties of raw materials can be detected by measuring weight, specific gravity, volume, volume, viscosity, etc., many of the physical properties often change regularly over time.
従来の固定した基準値を用いて重量検査する固定基準法
ては、その全体のデータをもとに重量平均値及び、標準
偏差から管理幅を求めるため、良品の合格範囲が広くな
り、不良品を良品として製品にするミスか生しやすい。In the conventional fixed standard method of weight inspection using a fixed standard value, the control range is determined from the weight average value and standard deviation based on the entire data, so the passing range for good products is wide and defective products are It is easy to make mistakes in making products as non-defective products.
これに反して、上述した本発明の移動平均値を用いる方
法は、原材料の経時的な変動に応答して管理幅を設定す
る基準値を変えるため、正常な範囲内ての変動(重量の
フレ)か基準値におりこまれ、その結果、基準値からの
重量のフレ幅か小さくなるので、従来法よりも管理幅を
狭く設定てき、それによって製品中に不良品が混入する
のを防止し、あるいはその可能性を最少限に減らすこと
がてきる。On the other hand, the method using the moving average value of the present invention described above changes the standard value for setting the control range in response to changes in raw materials over time, so fluctuations within the normal range (weight fluctuations) ) is incorporated into the standard value, and as a result, the range of weight deviation from the standard value becomes smaller, so the control range is set narrower than in the conventional method, thereby preventing defective products from being mixed into the product. , or reduce the possibility to a minimum.
本発明の方法についてさらに詳細に説明すると、本発明
においては、基本的には、良品の合格範囲を定めるため
の基準となる数値として、順次重量測定を行っている対
象製品て直前に重量を測定して良品と判定された複数の
製品の重量から計算した平均値、即ち、移動平均値を用
いて製品重量の良不良の判定を行う。この移動平均値を
求めるための良品製品のサンプル数は、少なくとも3個
あればよい。対象となる製品や原料における重量のバラ
ツキやフレ、包装形態か1個毎か複数個の集積体か等に
より異なるが、1個のデータの寄与度から、平均値を求
める製品サンプル数は20個以下て十分である。特に好
ましくは、3〜9である。このデータ数かあまりに多過
ぎると、たとえ移動平均を求めてもほとんど一定の値に
なり、従来の固定基準法と差かなくなる。To explain the method of the present invention in more detail, in the present invention, basically, the weight of the target product is measured immediately before the sequential weight measurement is performed as a reference value for determining the acceptable range of non-defective products. The average value calculated from the weights of a plurality of products determined to be non-defective products, that is, the moving average value, is used to determine whether the product weight is acceptable or defective. The number of samples of non-defective products for determining this moving average value should be at least three. The number of product samples to calculate the average value is 20 based on the degree of contribution of one piece of data, although it varies depending on the weight variations and fluctuations of the target product and raw materials, the packaging type, whether it is one piece or a collection of multiple pieces, etc. The following is sufficient. Especially preferably, it is 3-9. If this number of data is too large, even if a moving average is calculated, the value will be almost constant, and there will be no difference from the conventional fixed reference method.
また、従来の固定基準法ては、製品の重量平均値を中央
値とし、平均値を計算したときのデータから求めた重量
平均±3σを基に、重量不良の原因を考慮して良品の合
格範囲である管理幅を設定しているか、本発明ては、想
定される重量異常品(不良品)と基準値(移動平均値)
との重量差をrとしたときに、±rを管理幅とする。従
って、従来の固定基準法よりも管理幅を狭く設定するこ
とかてきる。この場合、上記合格範囲か製品の重量規格
等に適合する範囲内にあることは当然である。In addition, in the conventional fixed standard method, the weight average value of the product is taken as the median value, and based on the weight average ± 3σ obtained from the data when calculating the average value, the cause of the weight defect is taken into account and the product is passed. In the present invention, do you have a control band set within the range?
Let r be the weight difference between the two, and let ±r be the control width. Therefore, it is possible to set a narrower control range than in the conventional fixed standard method. In this case, it goes without saying that the above-mentioned acceptable range or the range that complies with the product weight standards, etc.
本発明を適用できる範囲は、1個毎に包装される製品の
場合ても、複数個の物品を集積して製品として包装され
る場合でもよく、製品の異常か重量の異常として検出で
きる全ての場合に適用することか可能である。その具体
例としては、内容量を個数表示しているか内容物の各々
が小さい製品、スピードか速くて内容物数量を目視検査
し難い製品、あるいは包装の中味か外部から見えない製
品、例えば、あめ、キャラメル等の菓子類、生理用タン
ポン、ナプキン、ポケットティシュ等の衛生用品に、好
適に適用することかできる。The scope to which the present invention can be applied is to products that are packaged individually or to products that are packaged together as a product. Is it possible to apply it in some cases? Specific examples include products whose contents are indicated by the number of pieces or each of the contents is small, products whose speed is too fast to visually inspect the contents, or products whose contents cannot be seen from the outside, such as candy. It can be suitably applied to confectionery such as caramel, sanitary products such as sanitary tampons, napkins, and pocket tissues.
[実施例]
第1図及び第2図には、製品の重量測定データの一例と
、本発明の方法に基づいて3個の製品重量から計算した
移動平均値(第1図)、及び20個の製品重量から計算
した移動平均値(第2図)を示している。[Example] Figures 1 and 2 show an example of product weight measurement data, a moving average value calculated from the weight of three products based on the method of the present invention (Figure 1), and a weight measurement data of 20 products. The moving average value calculated from the product weight (Figure 2) is shown.
第1図の場合は、移動平均値か製品重量のサンプルデー
タに対して適正な基準になっているが、第2図ては移動
平均値か製品重量のサンプルデータの変化に対して適正
に追従していない。しかしなから、前述したように、対
象となる製品や原料における重量のバラツキやフレ、包
装形態か1個毎か複数個の集積体か等により、20個の
製品重量の移動平均値を用いても、製品重量のサンプル
データに対して適正な基準にできる場合かある。In the case of Figure 1, the standard is appropriate for the sample data of the moving average value or product weight, but in Figure 2, the standard is properly tracked for changes in the sample data of the moving average value or product weight. I haven't. However, as mentioned above, depending on the weight variation and fluctuation of the target product and raw materials, the packaging type, whether it is one piece or multiple pieces, etc., the moving average value of 20 product weights is used. In some cases, this can also be used as an appropriate standard for sample data of product weight.
[発明の効果コ
以上に詳述したように、本発明の不良品検出方法によれ
ば、重量に起因する不良品を検知する管理幅を大幅に狭
くてきるので、市場に供給される製品中に不良品か混入
するのを防止し、あるいはその可能性を最少限に減らす
ことかできる。[Effects of the Invention] As detailed above, according to the defective product detection method of the present invention, the control range for detecting defective products due to weight can be significantly narrowed, so that It is possible to prevent or minimize the possibility of defective products being mixed into the product.
第1図および第2図は、製品の重量測定データの一例と
、本発明の方法に基づいて3個及び20個の製品重量か
ら計算した移動平均値を示すクラフである。
特許出願人 ライオン株式会社1 and 2 are graphs showing an example of product weight measurement data and moving average values calculated from 3 and 20 product weights based on the method of the present invention. Patent applicant Lion Corporation
Claims (1)
内にあるか否かを検査機構により検査し、良品と不良品
を区別して不良品を排除するに際し、 上記管理幅を設定する数値として、直前に重量を測定し
て良品と判定された3〜20個の製品の重量から計算し
た平均値を用い、それによって設定される管理幅により
製品重量の良不良の判定を行う、 ことを特徴とする生産ラインにおける不良品の検出方法
。[Claims] 1. When measuring the weight of a product to be produced and using an inspection mechanism to check whether the weight is within a control range, distinguishing good products from defective products and eliminating defective products, As the numerical value for setting the above control range, use the average value calculated from the weights of 3 to 20 products whose weights were recently measured and determined to be non-defective. A method for detecting defective products on a production line, characterized in that:
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
JP25342088A JPH0299834A (en) | 1988-10-07 | 1988-10-07 | Detection of defective article in production line |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
JP25342088A JPH0299834A (en) | 1988-10-07 | 1988-10-07 | Detection of defective article in production line |
Publications (1)
Publication Number | Publication Date |
---|---|
JPH0299834A true JPH0299834A (en) | 1990-04-11 |
Family
ID=17251144
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
JP25342088A Pending JPH0299834A (en) | 1988-10-07 | 1988-10-07 | Detection of defective article in production line |
Country Status (1)
Country | Link |
---|---|
JP (1) | JPH0299834A (en) |
Cited By (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
KR20190028166A (en) * | 2017-09-08 | 2019-03-18 | 김윤호 | Weight-sorting apparatus using a plurality of electronic scales |
JP2021144817A (en) * | 2020-03-11 | 2021-09-24 | 新明和工業株式会社 | Terminal crimp inspection device and update method for reference waveform of terminal crimp inspection |
Citations (1)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JPS5726716A (en) * | 1980-07-24 | 1982-02-12 | Yamato Scale Co Ltd | Weight sorting machine |
-
1988
- 1988-10-07 JP JP25342088A patent/JPH0299834A/en active Pending
Patent Citations (1)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JPS5726716A (en) * | 1980-07-24 | 1982-02-12 | Yamato Scale Co Ltd | Weight sorting machine |
Cited By (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
KR20190028166A (en) * | 2017-09-08 | 2019-03-18 | 김윤호 | Weight-sorting apparatus using a plurality of electronic scales |
JP2021144817A (en) * | 2020-03-11 | 2021-09-24 | 新明和工業株式会社 | Terminal crimp inspection device and update method for reference waveform of terminal crimp inspection |
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