JPH01180610A - Operation system for automated dolly in physical distribution - Google Patents
Operation system for automated dolly in physical distributionInfo
- Publication number
- JPH01180610A JPH01180610A JP63003164A JP316488A JPH01180610A JP H01180610 A JPH01180610 A JP H01180610A JP 63003164 A JP63003164 A JP 63003164A JP 316488 A JP316488 A JP 316488A JP H01180610 A JPH01180610 A JP H01180610A
- Authority
- JP
- Japan
- Prior art keywords
- dolly
- loading point
- point
- data
- loading
- 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
- 238000004364 calculation method Methods 0.000 claims abstract description 7
- 238000004519 manufacturing process Methods 0.000 claims description 5
- 238000000034 method Methods 0.000 description 12
- 238000010586 diagram Methods 0.000 description 4
- 230000000694 effects Effects 0.000 description 3
- 238000005516 engineering process Methods 0.000 description 1
- 238000011835 investigation Methods 0.000 description 1
Landscapes
- Control Of Position, Course, Altitude, Or Attitude Of Moving Bodies (AREA)
Abstract
Description
【発明の詳細な説明】
〔産業上の利用分野〕
二の発明は、プラントにおける生産ラインでの操業を最
適に運行するだめの物流自動化台車運行システムに関す
る。[Detailed Description of the Invention] [Industrial Application Field] The second invention relates to an automated logistics cart operation system for optimally operating a production line in a plant.
第３図は従来の物流自動化台車運行計画方法を示す台車
の運行サイクル説明図であり、図において、１１はスラ
ブなどの積込み点、１２は降し点、１３は台車の待ち時
間、１４は台車の走行時間を示しており、これによりＬ
Ｐ（輸送型問題）の多段適用により、効率的な輸送スケ
ジュールを実行しようとするものである。かかる台車の
運行サイクルにおいては、積込み開始から降し完了まで
は指示通りに台車が運行すると考えてよいので、スケジ
ューリングの自由度はない。従って、運行を効率化する
には、降し完了から積込み開始までの台車の配車スケジ
ュールの最適化を考える必要がある。従って、スケジュ
ーリング手法は時間軸を考慮したネットワークとしてモ
デル化し、これに上記輸送型問題を多段に適用している
。第４図はその一例を示す最適なスケジューリング手法
の概略を示す。具体的なアルゴリズムは、次の通りであ
る。FIG. 3 is an explanatory diagram of the operation cycle of a trolley showing a conventional distribution automation trolley operation planning method. In the figure, 11 is a loading point for slabs, etc., 12 is an unloading point, 13 is a waiting time for the trolley, and 14 is a trolley operation cycle. This shows the running time of L.
This is an attempt to implement an efficient transportation schedule by applying P (transportation type problem) in multiple stages. In the operation cycle of such a cart, it can be assumed that the cart operates according to instructions from the start of loading to the completion of unloading, so there is no flexibility in scheduling. Therefore, in order to make the operation more efficient, it is necessary to consider optimizing the trolley dispatch schedule from the completion of unloading to the start of loading. Therefore, the scheduling method is modeled as a network that takes the time axis into account, and the above-mentioned transportation problem is applied to this network in multiple stages. FIG. 4 shows an outline of an optimal scheduling method as an example thereof. The specific algorithm is as follows.
手順１．） ステップｋを考えて降し完了し、待機中
の台車のグループを７にとし、各台車で積込み可能なス
ラブのグループを＄６とする。Step 1. ) The unloading is completed considering step k, and the number of waiting truck groups is 7, and the number of slab groups that can be loaded by each truck is $6.
ここで、７に＝ （’ｌ’、に、７’ｔｋ・・・・・・
、’ｒ、”、・・・・・・７’ｆｉｋ）の各要素は、降
し完了時刻と待機場所の属性をもち、＄に＝（Ｓ、に、
８２ｋ・・・・・・３ 、ｋ。Here, to 7 = ('l', to, 7'tk...
, 'r,'',...7'fik) has the attributes of unloading completion time and waiting location, and $ = (S, to,
82k...3,k.
・・・・・・３．ｋ）の各要素は積込み予定時刻と場所
の属性をもつ。・・・・・・3. Each element in k) has attributes of scheduled loading time and location.
但し、この時Ｓ” ＝＄”ｎ＄１なる積込みフラグがあ
ればステップに−１での該当スラブへの配車を取り消し
てＴｋを再セットする。However, at this time, if there is a loading flag of S''=$''n$1, the dispatch to the corresponding slab at step -1 is canceled and Tk is reset.
手順２．） Ｔ’から＄にへの台車の運行所要時間Ｃ
ｉ ｊを設定して、運行トータル時間（＝距離）ｊ
但し、ｉは台車の順位番号、Ｎα、ｊは対象となる積込
予定スラブの順位番号を示す。Step 2. ) Required time C for the trolley to travel from T' to $.
i j is set, and the total operation time (=distance) j is obtained. However, i is the rank number of the trolley, and Nα and j are the rank numbers of the target slabs to be loaded.
Ｘ ｉ ｊは１又はＯとし、台車Ｔ♂がスラブＳ：を積
込むときＸｚ７＝１とする。X ij is set to 1 or O, and when the truck T♂ loads the slab S:, Xz7=1.
従来の物流自動化台車運行計画方法は、以上のように実
施されるので、台車の配車スケジュールを最適化するこ
とができるが、台車毎の位置関係等、他台車との関係づ
けがされていないので、衝突問題等を発生するなどの問
題点があった。Conventional logistics automation trolley operation planning methods are carried out as described above, making it possible to optimize the trolley dispatch schedule. , there were problems such as collision problems.
この発明は、上記のような問題点を解消するためになさ
れたもので、台車の移動距離および積込み点での待ち時
間を最小にできるとともに、他台車との衝突を防止でき
る物流自動化台車運行システムを得ることを目的とする
。This invention was made to solve the above-mentioned problems, and provides an automated logistics trolley operation system that can minimize the travel distance of the trolley and the waiting time at the loading point, as well as prevent collisions with other trolleys. The purpose is to obtain.
この発明に係る物流自動化台車運行システムは、台車実
データ把握手段によって実ラインから実動台車の現状を
把握し、その実動台車のうち降し台車状態にある台車の
みを降し台車計算手段によって計算し、上記実ラインか
ら積込み点データ把握手段によって積込み点の現状を把
握し、上記降し台車計算手段および積込み点データ把握
手段の各出力データにもとづき、最適ルール決定手段に
よって、降し完了より次積込み点までの台車の移動距離
および積込み点での待ち時間を最小とする最適ルールを
決定するとともに、次台車との衝突いかんをシミュレー
タを用いて確認できるような構成としたものである。The automated logistics trolley operation system according to the present invention grasps the current state of the active bogies from the actual line using the bogie actual data grasping means, calculates only the bogies in the unloading state of the active bogies by the unloading bogie calculation means. Then, the current state of the loading point is grasped from the above-mentioned actual line by the loading point data grasping means, and based on each output data of the above-mentioned unloading truck calculation means and loading point data grasping means, the optimal rule determining means determines the next step after unloading is completed. The system determines the optimal rule that minimizes the travel distance of the cart to the loading point and the waiting time at the loading point, and uses a simulator to check whether there will be a collision with the next cart.
この発明における物流自動化台車運行システムは、台車
の目的点到達データと、積込み点データとの組み合わせ
にもとづき、最適ルール決定手段によって、台車の移動
距離を最小にするための移動パターンを求めるとともに
移動経路を調査することにより、他台車との衝突を防止
しながら最適な輸送計画を行なえるようにする。The automated logistics trolley operation system of the present invention uses an optimal rule determining means to determine a movement pattern that minimizes the travel distance of the trolley based on a combination of destination point arrival data of the trolley and loading point data, and also determines the movement route. By investigating this, it is possible to carry out optimal transportation planning while preventing collisions with other trolleys.
以下、この発明の一実施例を図について説明する。第１
図において、１は実ラインより全実動台車の現状を把握
して格納する台車実データ把握手段、２は上記全実動台
車のうち降し台車状態となっている台車のみを計算によ
って求める降し台車計算手段、３は上記台車に関しての
データを取り込むと同時に、全積込み点の現状を把握す
る積込み点データ把握手段、４は降し台車計算手段２お
よび積込み点データ把握手段３の各出力データにもとづ
いて、降し完了後の次積込み点を決定するのに最適なル
ールを決定する最適ルール決定手段、５は次台車との衝
突状態をシミュレーションによって石奮Ｊ忍するシミュ
レータである。An embodiment of the present invention will be described below with reference to the drawings. 1st
In the figure, 1 is a bogie actual data grasping means that grasps and stores the current state of all production bogies from the actual line, and 2 is a bogie data grasping means that calculates only the bogies that are in the unloading state among all the production bogies. Reference numeral 3 indicates loading point data grasping means for capturing the data regarding the above-mentioned trolleys and grasping the current status of all loading points; 4 indicates each output data of the unloading trolley computing means 2 and the loading point data grasping means 3; 5 is a simulator for simulating the collision state with the next truck.
次に動作について説明する。Next, the operation will be explained.
上記最適なルールを決定するための方法は、降し完了よ
り次積込み点までの移動距離及び積込み点での待ち時間
が最小となるものを求めることによって行われる。The method for determining the optimal rule is to find the one that minimizes the travel distance from the completion of unloading to the next loading point and the minimum waiting time at the loading point.
次に最適なルールを最適ルール決定手段４によって決定
する方法について具体的に述べる。まず、台車実データ
把握手段１によって得た降し状態である台車位置をＸ、
積込み点データ把握手段３によって得た積込み点位置を
（Ｙｌ、Ｙｚ、・・・・・・Ｙ、）とおき、ＸからＹｌ
までの距離をＤｘｙｔ 、ＸからＹ２までの距離をＤ０
２、順次ＤＸＹＩ・・・・・・ＤＸ□とする。なお、ｎ
は積込み点数を示す。Ｘからの距離の集合（Ｄ ｘｖｌ
、 Ｄ ｘｖ□、・・・・・・Ｄｘ□）を値の小さいも
のから並びかえ、（ＤＸ□Ｉ＋ＤＸ□２．・・・・・・
Ｄｘｚ−）とする。Next, a method for determining the optimal rule by the optimal rule determining means 4 will be specifically described. First, the position of the cart, which is the unloaded state obtained by the cart actual data grasping means 1, is expressed as
Let the loading point position obtained by the loading point data grasping means 3 be (Yl, Yz,...Y,), and move from X to Yl.
The distance from X to Y2 is Dxyt, and the distance from X to Y2 is D0
2.Sequentially DXYI...DX□. In addition, n
indicates the number of loading points. Set of distances from X (D xvl
, D xv□,...Dx□) from the smallest value, (DX□I+DX□2.....
Dxz-).
但し、ｚ＝ｙ、・・・・・・Ｙ、である。However, z=y,...Y.
移動距離が最小となるものが最適なルール始点となるの
で、２．．２．・・・・・・から優先される。Ｘ地点の
対象台車の降し完了より積込み点までの移動時間と、積
込み対象点での対象台車の降し完了より積込み可能まで
の時間がほぼ一致するものより優先とし、（ＴＸ□’、
、Ｔ、□′２．・・・・・・ＴＸ２’１１ ）とする。The optimal rule starting point is the one with the minimum movement distance, so 2. ．． 2. Priority is given to... Priority is given to the travel time from the completion of unloading of the target trolley at point X to the loading point, and the time from the completion of unloading of the target trolley at the target loading point to the time until loading is almost the same, and (TX□',
, T, □′2. ...TX2'11).
次に、Ｚｌ＝Ｚ′ｊ ｉ、ｊ：１・・・・・・ｎ、とな
る地点で、距離的にも時間的にも優先順位の高いものか
ら、対象台車における最適な次ルールとする。Next, at the point where Zl=Z'j i, j: 1...n, select the next rule that is most suitable for the target truck, starting from the one with the highest priority in terms of distance and time. .
しかしながら、この方法は、対象台車のみを考えての最
適解であり、他台車とのバランスを考える必要がある。However, this method is an optimal solution considering only the target truck, and it is necessary to consider the balance with other trucks.
従って、最適ルール決定手段４によって決定されたルー
ルと、他台車の動きを確認するため、シミュレータ５に
おいて、実際の動きと同様な考え方で次台車が計算対象
となるまで確認し、衝突がなければルールをラインへ指
示し、衝突がおこれば最適ルール決定手段４にもどり、
対象台車の降し地点よりの積込み点への出発時間や、人
優先順位のものを再決定する等の再計算を行ない、シミ
ュレータ５にもどす。Therefore, in order to confirm the rules determined by the optimal rule determining means 4 and the movement of other bogies, the simulator 5 checks the movement of the next bogie using the same concept as the actual movement, and if there is no collision. Instruct the rules to the line, and if a collision occurs, return to the optimal rule determining means 4,
Recalculations such as the departure time from the unloading point to the loading point of the target trolley and re-determination of the priority order of people are performed, and the process is returned to the simulator 5.
第２図は上記動作のアルゴリズムをわかり易く説明した
フロ、−チャートであり、これを以下に簡単に説明する
。時間きざみは、台車が目的点に到達することとし、現
状の台車の位置を調査しくステップ５Ｔ１）、さらに目
的到達点の台車を取り出す（ステップ５Ｔ２）。続いて
積込み点を調べる（ステップ５Ｔ３）。ここで、最適な
運行計画とは台車の移動距離を最小にすることである。FIG. 2 is a flowchart that clearly explains the algorithm for the above operation, which will be briefly explained below. As for the time increments, it is assumed that the cart reaches the destination point, the current position of the cart is investigated (step 5T1), and the cart at the destination point is taken out (step 5T2). Next, the loading point is checked (step 5T3). Here, the optimal operation plan is to minimize the moving distance of the trolley.
故に、目的点での台車と積込み点との移動時間（又は距
離）を求め、最小の値となる積込み点へ移動する候補と
する（ステップ５Ｔ４）。但し、積込み点が重複した場
合、重複した両台車について計算をする計算対象の台車
について、それぞれに衝突調査をする（ステップ５Ｔ５
）。調査方法として、始点から終点の経路はルール化に
より計算可能としてお（。それぞれに移動途中で同地点
及び同時間内のものがある場合、繰り返し計算を行う（
ステップ５Ｔ７）。なお、ステップＳＴ５に次いで、計
算対象外の台車についても、衝突チエツクを行い（ステ
ップ５Ｔ６）、続いてステップＳエフ以降を実行する。Therefore, the travel time (or distance) between the cart and the loading point at the destination point is determined, and the loading point with the minimum value is selected as a candidate for movement (step 5T4). However, if the loading points overlap, a collision investigation is performed for each of the trolleys to be calculated for both overlapping trolleys (step 5T5).
). As a survey method, the route from the start point to the end point can be calculated by creating rules (.If there are routes at the same point and within the same time during each journey, calculations are repeated (
Step 5T7). Incidentally, following step ST5, a collision check is also performed for carts that are not subject to calculation (step 5T6), and then steps SF and subsequent steps are executed.
なお、上記台車運行方法は実ラインとのオンラインでも
、あるいはあらかじめ計算しておくオフラインにも適用
できる。The above bogie operation method can be applied online to the actual line, or offline by calculating in advance.
〔発明の効果］
以上のように、この発明によれば、最適ルール決定手段
によって、台車の目的点到達データと積込み点データと
にもとづき、台車の移動距離を最小にするためのパター
ンを求めるように構成したので、台車の待ち時間を最小
にできるとともに、他台車との衝突を未然に防止でき、
効率的に物流自動化を図ることができるものが得られる
効果がある。[Effects of the Invention] As described above, according to the present invention, the optimal rule determining means determines a pattern for minimizing the travel distance of the trolley based on the destination point arrival data of the trolley and the loading point data. This structure minimizes the waiting time for the trolley and prevents collisions with other trolleys.
This has the effect of being able to efficiently automate logistics.
第１図はこの発明にかかる物流自動化台車運行システム
を示すブロック接続図、第２図は台車運行方法を説明す
るフローチャート、第３図は従来の台車の運行サイクル
図、第４図は従来の運行スケジューリング手法を示す説
明図である。
■は台車実データ把握手段、２は降し台車計算手段、３
は積込み点データ把握手段、４は最適ルール決定手段。
第２マFig. 1 is a block connection diagram showing the logistics automated trolley operation system according to the present invention, Fig. 2 is a flowchart explaining the trolley operation method, Fig. 3 is a conventional cart operation cycle diagram, and Fig. 4 is the conventional operation. FIG. 2 is an explanatory diagram showing a scheduling method. ■ means to grasp the actual data of the bogie, 2 means to calculate the unloading bogie, 3
4 is a loading point data grasping means, and 4 is an optimal rule determining means. 2nd ma
Claims (1)
把握手段と、この台車実データ把握手段に格納した実動
台車のうち降し台車状態にある台車のみを計算する降し
台車計算手段と、上記実ラインから積込み点の現状を把
握する積込み点データ把握手段と、上記降し台車計算手
段および積込み点データ把握手段の各出力データにもと
づいて、降し完了より次積込み点までの台車の移動距離
および積込み点での待ち時間を最小とする最適ルールを
決定する最適ルール決定手段と、対象台車の降し点から
積込み点への出発時点や次優先順位を決定するために、
次台車との衝突いかんを確認するシミュレータとを備え
た物流自動化台車運行システム。a bogie actual data grasping means for grasping the current state of the production bogies from the actual line; a dropping bogie calculation means for calculating only the bogies in the dismounting bogie state among the production bogies stored in the bogie actual data grasping means; Based on the loading point data grasping means for grasping the current state of the loading point from the above-mentioned actual line, and each output data of the above-mentioned unloading bogie calculation means and loading point data grasping means, the bogie is moved from the completion of unloading to the next loading point. Optimal rule determining means for determining the optimal rule that minimizes the distance and waiting time at the loading point, and the departure point and next priority of the target truck from the unloading point to the loading point.
An automated logistics truck operation system equipped with a simulator that checks whether there will be a collision with the next truck.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| JP63003164A JPH01180610A (en) | 1988-01-12 | 1988-01-12 | Operation system for automated dolly in physical distribution |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| JP63003164A JPH01180610A (en) | 1988-01-12 | 1988-01-12 | Operation system for automated dolly in physical distribution |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| JPH01180610A true JPH01180610A (en) | 1989-07-18 |
Family
ID=11549717
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| JP63003164A Pending JPH01180610A (en) | 1988-01-12 | 1988-01-12 | Operation system for automated dolly in physical distribution |
Country Status (1)
| Country | Link |
|---|---|
| JP (1) | JPH01180610A (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2006154907A (en) * | 2004-11-25 | 2006-06-15 | Matsushita Electric Works Ltd | Travel control device |
| WO2018116718A1 (en) * | 2016-12-22 | 2018-06-28 | シャープ株式会社 | Cargo transport system and automated guided vehicle |
-
1988
- 1988-01-12 JP JP63003164A patent/JPH01180610A/en active Pending
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2006154907A (en) * | 2004-11-25 | 2006-06-15 | Matsushita Electric Works Ltd | Travel control device |
| WO2018116718A1 (en) * | 2016-12-22 | 2018-06-28 | シャープ株式会社 | Cargo transport system and automated guided vehicle |
| US11543818B2 (en) | 2016-12-22 | 2023-01-03 | Sharp Kabushiki Kaisha | Cargo transport system and automated guided vehicle |
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