GB2610032A - Method for scheduling hybrid flow shop comprising variable parameter continuous processing and intermittent processing - Google Patents

Method for scheduling hybrid flow shop comprising variable parameter continuous processing and intermittent processing Download PDF

Info

Publication number
GB2610032A
GB2610032A GB2208781.1A GB202208781A GB2610032A GB 2610032 A GB2610032 A GB 2610032A GB 202208781 A GB202208781 A GB 202208781A GB 2610032 A GB2610032 A GB 2610032A
Authority
GB
United Kingdom
Prior art keywords
processing
time
workpiece
transport
stage
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
Application number
GB2208781.1A
Other versions
GB202208781D0 (en
Inventor
Liu Zhifeng
Yan Jun
Zhang Caixia
Chu Hongyan
Dong Shulin
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Beijing University of Technology
Original Assignee
Beijing University of Technology
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Beijing University of Technology filed Critical Beijing University of Technology
Publication of GB202208781D0 publication Critical patent/GB202208781D0/en
Publication of GB2610032A publication Critical patent/GB2610032A/en
Pending legal-status Critical Current

Links

Classifications

    • GPHYSICS
    • G05CONTROLLING; REGULATING
    • G05BCONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B19/00Programme-control systems
    • G05B19/02Programme-control systems electric
    • G05B19/418Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS] or computer integrated manufacturing [CIM]
    • G05B19/41865Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS] or computer integrated manufacturing [CIM] characterised by job scheduling, process planning, material flow
    • GPHYSICS
    • G05CONTROLLING; REGULATING
    • G05BCONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B2219/00Program-control systems
    • G05B2219/30Nc systems
    • G05B2219/32Operator till task planning
    • G05B2219/32252Scheduling production, machining, job shop
    • YGENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02PCLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
    • Y02P90/00Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
    • Y02P90/02Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]

Landscapes

  • Engineering & Computer Science (AREA)
  • General Engineering & Computer Science (AREA)
  • Manufacturing & Machinery (AREA)
  • Quality & Reliability (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Automation & Control Theory (AREA)
  • General Factory Administration (AREA)
  • Management, Administration, Business Operations System, And Electronic Commerce (AREA)

Abstract

A method for scheduling a hybrid flow shop comprising variable parameter continuous processing and intermittent processing. Processing stage types of a shop scheduling model are analyzed; two types of processing stages, i.e., a variable parameter continuous processing stage and an intermittent processing stage, are built; a hybrid flow shop scheduling model comprising different types of processing stages is built. The model is built in the following steps: building hypothesis and requirements of the scheduling model; analyzing and building a temporal relation network of a workpiece/a manufacturing device/a transport device; building a completion time mathematical model and a quality model of a hybrid flow shop; and building a multi-objective function of the hybrid flow shop scheduling model. Therefore, completion time and quality multi-objective models are built for a hybrid flow shop, and the problem of scheduling of the hybrid flow shop comprising continuous processing and intermittent processing is solved by using the models.

Description

METHOD FOR SCHEDULIING HYBRID FLOW SHOP COMPRISING VARIABLE PARAMETER CONTINUOUS PROCESSING AND INTERMITTENT PROCESSING
PARAMETERS
TECHNICAL FIELD
[0001] The present disclosure relates to hybrid flow-shop scheduling techniques, in particular to a method for establishing a hybrid flow-shop scheduling model featuring continuous processing and intermittent processing with variable parameters, and belongs to the technical field of advanced manufacturing control and scheduling.
BACKGROUND
[0002] Hybrid Flow-shop Scheduling Problem (HFSP) is widely present in actual manufacturing shops. However, at present, most of the production processes are based on intermittent machining production process, in which a waiting time is set between two successive processing stages to realize the reasonable arrangement of a processing task. In addition to cold working process such as machining production process, a hot working process is commonly found among various kinds of cold working processes. Different from the intermittent cold working process, the hot working process is featured by forced continuous processing, for example two-stage processing procedure involving a heating by a heating furnace and a heat treatment, in which a workpiece heated by the heating furnace must be subjected to the heat treatment immediately and intermittently, to allow the workpiece to be heated at a required high temperature. At present, in a hybrid production process, such continuous processing procedures can only be performed individually in batches, resulting in low processing efficiency.
[0003] Further, in addition to the difficulties caused by a continuous processing such as heat treatment in production scheduling, individual batch processing mode can also solve the problem that the processing quality is difficult to control in a continuous processing procedure such as heat treatment, especially when workpieces are in a heating furnace and other apparatus, during which heating and holding time directly affects the processing quality of the workpieces. Therefore, in order to achieve efficient and high-quality processing in hybrid flow shop, it is of great value to study a hybrid flow shop scheduling model featuring continuous processing and intermittent processing with variable parameters from the point of view of completion time and processing quality.
SUMMARY
[0004] The present disclosure, with the object of pursuing high efficiency and high quality required in actual production, takes the state of workpiece, manufacturing apparatus and transport apparatus at different production processes into consideration. A continuous production process with variable parameters and an intermittent production process with variable parameters are designed, to solve the problems existing in a continuous processing such as heat treatment and cold processing, respectively. A production scheduling model targeting completion time and manufacturing quality is established.
[0005] The present disclosure adopts the following technical solution: a scheduling method for a hybrid flow shop featuring a continuous processing and an intermittent processing with variable parameters, where the essential requirements of the scheduling method are as follows: 100061 1) composition: a raw material storage area, a finished product storage area, m processing stages (m>2); (m+ I) transport stages; [0007] 2) each of the processing stages adopting one or more identical manufacturing apparatus; [0008] 3) each of the transport stages adopting one or more identical transport apparatus (each transport stage usually adopting one transport apparatus due to limited transport space); [0009] 4) in the manufacturing process, n jobs, m processing stages for processing, and (m+1) transport stages for transporting being involved; [0010] 5) each manufacturing apparatus only handling one job at a time; 100111 6) each transport apparatus only transporting one job at a time; [0012] 7) each workpiece only be handled by one manufacturing apparatus or one transport apparatus at a time; [0013] 8) the processing stage mainly consisting of two types of processing: the continuous processing with variable parameters, and the intermittent processing with the variable parameters; [0014] 9) in the continuous processing stage with the variable parameters, it being required that when processing is about to be completed in this stage, there is a variable parameter within a domain of definition [c, cl], and this parameter may be adjusted in the scheduling plan to ensure that a variety of hybrid processing parts are able to be arranged reasonably to be processed; and [00151 10) in the intermittent processing stage with variable parameters, it is required that when processing is completed in this stage, waiting time before transport and waiting time before processing in the next stage are adjusted to ensure reasonable and efficient production scheduling, and the waiting time being adjusted within a domain of definition [0. +-c].
[0016] The method is implemented in the following processes.
Si, building a time relationship network of workpieces/manufacturing apparatus/transport apparatus.
[0017] The workpieces. manufacturing apparatus and transport apparatus are in various kinds of states in the processing stage, and a variety of different time factors are adopted to express the states in the processing stage of the workpieces, manufacturing apparatus, and transport apparatus. Time relationships of the workpieces/manufacturing apparatus/transport apparatus are shown in FIG. 2. In FIG. 2, time factors related to each workpiece include: a waiting time before transport re, a transport time 71, a waiting time before processing rP, a preparation time r, a processing time 71', and an adjustment time r, where when a processing stage is the continuous processing with variable parameters, the waiting time before transport and waiting time before processing at a latter processing stage are both zero, and the variable parameter is an adjustment time of this stage, and when the processing stage is the intermittent processing, the waiting time is able to be adjusted to make a scheduling plan reasonably; time factors related to processing apparatus include: a processing apparatus gap time 7g, a preparation time Tr, a processing time r, and an adjustment time T; and time factors related to transport apparatus include: a transport apparatus gap time r and a preparation time Ti When the workpiece is processed on the manufacturing apparatus, the preparation time of the workpiece is equal to that of the manufacturing apparatus, the processing time of the workpiece is equal to that of the manufacturing apparatus, and the adjustment time of the workpiece is equal to that of the manufacturing apparatus. When the workpiece is transported on the transport apparatus, the transport time of the workpiece is equal to that of the transport apparatus.
S2, constructing a completion time model of a hybrid flow shop.
[0018] Where a mathematical completion time model of the hybrid flow shop is established, the completion time of a single workpiece is a time from the moment when the workpiece starts to be processed to the completion of the last processing procedure. Assuming that the processing time of all the workpieces starts from the time t=0, then the completion time of the whole batch of workpieces is the maximum value of the completion time of all the single workpieces in the batch. There are two processing stages in the hybrid flow shop, namely, a continuous processing with variable parameters and an intermittent processing with variable parameters, the constructed mathematical completion time model is as follows: [0019] C = max E(T,:' * +77 Do_o+T,1 + To° + Tv') (i = I, 2,3, * * .,n) s.t.
100201 777' = tt, -St, [0021] = rt, -tt,, [0022]wtt < W it
YJ
[0023] rt [0024] et,, = [0025] etu = = tt,Ho (D = 0) (7) [0026] we = rt"(D), =0) (8) [0027] 7-; =ety -suty =hT" * 0 -D + eT; * Di (9) [0028] hT:'" far (10).
[0029] Where equation (I) denotes the mathematical model targeting completion time, and equations (2)-(10) denote constraint conditions. Specifically, equation (2) denotes a constraint of variable waiting time before transport. Equation (3) denotes a constraint of variable waiting time before processing. Equation (4) denotes a sequential relationship constraint between two adjacent workpieces on the same transport apparatus. Equation (5) denotes a sequential relationship constraint between two adjacent workpieces on the same processing apparatus. Equation (6) denotes a relationship between two processing stages of the same workpiece. Equation (7) denotes a relationship between two production processes for a same workpiece before transport when the previous processing stage is continuous processing. Equation (8) denotes a relationship between two production processes for a same workpiece after transport when the previous process is continuous processing. Equation (9) denotes a definition of adjustment time for different types of processing stages, and equation (JO) denotes a constraint of the variable adjustment time between maximum and minimum values.
53, constructing a processing quality model of a hybrid flow shop [00301 Regarding a continuous processing with variable parameters in the hybrid flow shop model, a continuous processing is implemented by setting the adjustment time as a variable parameter. In an actual production, a continuous processing such as heat treatment mainly is implemented mainly through a heating furnace apparatus, the adjustment time is the heating and holding time of the workpiece which directly reflects the processing quality of the workpiece. In the actual processing, the holding time is a numerical value within a range under process requirements, and the optimal holding time is a value between the minimum holding time and the maximum holding time. To ensure the best quality of the workpiece after heating, an optimal holding time gap value is set within a holding time range under process requirements, to optimize the holding time gap and thus improve the heating quality of forgings. The optimal holding time gap value being expressed as: [0031] hgri, = (hi; hr:)(1 D i) (II).
100321 By calculating a mean square error of an actual scheduling holding time and an optimal holding time, the difference between the actual holding time and the optimal holding time of the workpiece is reflected, and a sum of mean square errors of optimal holding time gaps of all workpieces is established to construct the following quality model in hybrid production: I " \ 2 [0033] = -hT,h) 1)1 (12). n. h
S4, constructing a multi-objective function of a hybrid flow shop scheduling model. [0034] Aiming at the completion time model and the quality model of the hybrid flow shop scheduling model for continuous processing with variable parameters and intermittent processing with variable parameters, a multi-objective scheduling optimization model is established, so as to perform scheduling optimization from efficiency and quality both. Where, the efficiency is reflected by the completion time, and the quality is reflected by the optimal holding time gap. A multi-objective optimization equation established is described as follows: [0035] T = max f = min(T, Q) (13) [0036] E (To" * Do _0+ To' -To" . Do,)+77,1 + Tr + 711) [ J=1 (i =1,2,3,***, n) (14) = Ez[(hpTo -hp To'' )2. 0 -DJ)] Q -n h [0037] s.t.
[0038] T111 =re, -sr (15) 100391 Ty." = -tto (16) [0040] ay, < (17) [0041] et r rt, (18) 10042] et " = st",,A) (19) 100431 et = Sc j+,) = etoi+1) (D = 0) (20) [0044] rt" =-0) (21) 100451 7 =e -sut =hT D)+ el" * D (22) [0046] Ur" hi; hT,,'"" (23) 100471 the symbols used in the model are detailed as follows: Symbol Definition Number of workpieces Serial number of each workpiece, i = I, 2, ..., n in Number of processing stages Serial number of each processing stage, j -1, 2, ..., in Serial number of a workpiece previous to workpiece i on the same manufacturing apparatus Serial number of a workpiece previous to workpiece i on the same transport apparatus 0 indicates that processing stage/ is a continuous processing; D, = 1 indicates that processing stage j is an intermittent processing Number of a continuous processing stages across the whole production line C,"," Maximum completion time Waiting time before transport of workpiece i in processing stage] Transport time of workpiece i in processing stage/ TWI, Waiting time before processing of workpiece i in processing stage] T' Preparation time of workpiece i in processing stage] Processing time of workpiece i in processing stage] Adjustment time of workpiece i in processing stage] Gap time between manufacturing the workpiece i and the previous workpiece on the same 71; manufacturing apparatus in processing stage] Gap time between transporting of the workpiece i and the previous workpiece on the same transport apparatus in processing stage] st" Start time moment of workpiece i in processing stage] It,, Transport start time of workpiece i in processing stage] wt" Start time moment of waiting time before processing of workpiece i in processing stage] rt" Start time moment of preparation time of workpiece i in processing stage/ pt," Processing start time moment of workpiece i in processing stage] sut,, Start time moment of adjustment time of workpiece i in processing stage] End time moment of workpiece i in processing stage] Adjustment time of workpiece i in processing stage], when the processing apparatus is a en, machining apparatus hT" Heating and holding time of workpiece i in processing stage] hlr Allowable maximum value of heating and holding time of workpiece i in processing stage] hT7in Allowable minimum value of heating and holding time of workpiece i in processing stage] Optimal heating and holding time of workpiece i in processing stage] Absolute difference between actual heating and holding time and optimal heating and holding hgT,, time of workpiece i in processing stage] Mean square error between actual heating and holding time and optimal heating and holding time ilgTVISE of workpiece i in processing stage j 100481 In the present disclosure, two types of processing stages including continuous processing with variable parameters and intermittent processing with variable parameters of the hybrid flow shop scheduling model are analyzed and confirmed. Scheduling processing methods in the two processing stages are analyzed. A hybrid flow shop scheduling model consisting of different types of processing stages is established. Based on the scheduling model, a multi-objective optimization function aiming at completion time and quality is established. A model corresponding to a scheduling optimization algorithm for solving shop scheduling problem is provided.
BRIEF DESCRIPTION OF THE DRAWINGS
[0049] The present disclosure will be further described below in conjunction with the accompanying drawings and embodiments.
[0050] FIG. 1 is a schematic diagram of a hybrid production mode for continuous processing and intermittent processing with variable parameters.
[0051] FIG. 2 is a diagram illustrating multiple time relationships of workpieces/manufacturing apparatus/transport apparatus.
DETAILED DESCRIPTION OF THE EMBODIMENTS
[0052] In order to achieve the objectives of high efficiency and high quality required in actual production, in consideration of the states of workpieces, processing apparatuses and transport apparatuses at different manufacturing stages, the present disclosure designs a continuous processing stage with variable parameters and an intermittent processing stage with variable parameters, for dealing with a continuous processing such as heat treatment and cold processing processes, respectively, and establishes a production scheduling model targeting completion time and manufacturing quality. The present disclosure is further described below in combination with accompanying drawings and specific examples: Step 1: building hypothesis and requirements of a scheduling model.
[0053] As shown in FIG. 1, a hybrid shop scheduling model under a two-phase processing mode is described. Materials start from a raw material storage area, pass through various processing stages in turn, and finally arrive at a finished product storage area. The hypothesis and requirements of the scheduling model are as follows: [0054] 1) thc model is composed of: a raw material storage area, a finished product storage area, m processing stages (m>2) and (m+1) transport stages; [0055] 2) each of the processing stages adopts one or more identical manufacturing apparatuses; [0056] 3) each of the transport stages adopts one or more identical transport apparatuses (each transport stage usually adopts one transport apparatus due to limited transport space); [0057] 4) in the manufacturing process, n jobs are processed at m processing stages, and arc transported at (m+1) transport stages; [0058] 5) each manufacturing apparatus can only handle one job at a time: 100591 6) each transport apparatus can only transport one job at a time; [0060] 7) each workpiece can only be handled by one manufacturing apparatus or one transport apparatus at a time: [0061] 8) the processing stage mainly includes two types of processing: a continuous processing with variable parameters, and an intermittent processing with variable parameters; [0062] 9) in the continuous processing stage with variable parameters, it is required that when processing is about to be completed in this stage, a variable parameter within a domain of definition [c, d] can be adjusted in a scheduling plan, to ensure that a variety of hybrid processing parts can be arranged reasonably to be processed; and [0063] 10) in the intermittent processing stage with variable parameters, it is required that when processing is completed in this stage, waiting time before transport and waiting time before processing for the next stage are adjusted to ensure a reasonable and efficient production scheduling, in which the waiting time may be adjusted within a domain of definition [0,-Fr/4 Step 2: building a time relationship network of workpieces/processing apparatuses/transport apparatuses.
[0064] The workpieces, manufacturing apparatuses and transport apparatuses are in various kinds of states in the production process, and a variety of different time factors are adopted to characterize the states in the production process of the workpieces, manufacturing apparatus, and transport apparatus.
[0065] As shown in FIG. 2, multiple time relationships of workpieces, manufacturing apparatus and transport apparatus are described. In FIG. 2, time factors related to a workpiece include: a waiting time before transport r, a transport time i, a waiting time before processing rP, a preparation time Tf, a processing time TP, and an adjustment time T. When a processing stage adopts a continuous processing with variable parameters, the waiting time before transport and waiting time before processing at the latter stage are both zero, and the variable parameter is the adjustment time of this stage: and when the processing stage adopts an intermittent processing, the waiting time can be adjusted to make a scheduling plan reasonably. Time factors related to processing apparatus include: a processing apparatus gap time Tg, a preparation time r. a processing time TP, and an adjustment time r; and time factors related to transport apparatus include: a transport apparatus gap time r and a preparation time Tr. When the workpiece is processed on the manufacturing apparatus, the preparation time of the workpiece is equal to that of the manufacturing apparatus, the processing time of the workpiece is equal to that of the manufacturing apparatus, and the adjustment time of the workpiece is equal to that of the manufacturing apparatus. When the workpiece is transported on the transport apparatus, the transport time of the workpiece is equal to that of the transport apparatus; Step 3: constructing a mathematical completion time model of a hybrid flow shop. 10066] A mathematical completion time model of the hybrid flow shop is established, the completion time of a single workpiece is a time from the moment when the workpiece starts to be processed to the completion of the last processing procedure. Assuming that the processing time of all the workpieces starts from the time t=0, then the completion time of the whole batch of workpieces is the maximum value of the completion time of all the single workpieces in the batch. There are two processing stages in the hybrid flow shop, namely, a continuous processing with variable parameters and an intermittent processing with variable parameters, the constructed mathematical completion time model is as follows: [0067] C = max 1(77' )+7+7 13(0+Turs +71 (i= 1, 2, 3, * * * , n) (1)
_
[0068] s.t.
[0069] Tu"' =tt,-st, (2) [0070] T"HP = (3) [0071] tt" < wt,o (4) [0072] et,"rt, (5) [0073] et =51,(1,) (6) [0074] et =51,,,)= ,(1") (DI= 0) (7) [0075] wto =rt,/(D,,= 0) (8) [0076] J7 = -sut, =117;, . -DI)+ (9) [0077] h7:1"" h7/h7,7- (10).
[00781 Where equation (1) denotes the mathematical model targeting completion time, and equations (2)-(10) denote constraint conditions. Specifically, equation (2) denotes a constraint of variable waiting time before transport. Equation (3) denotes a constraint of variable waiting time before processing. Equation (4) denotes a sequential relationship constraint between two adjacent workpieces on the same transport apparatus. Equation (5) denotes a sequential relationship constraint between two adjacent workpieces on the same processing apparatus. Equation (6) denotes a relationship between two processing stages of the same workpiece. Equation (7) denotes a relationship between two production processes for a same workpiece before transport when the previous production process is continuous processing. Equation (8) denotes a relationship between two production processes for a same workpiece after transport when the previous process is continuous processing. Equation (9) denotes a definition of adjustment time for different types of processing stages, and equation (10) denotes a constraint of the variable adjustment time between maximum and minimum values.
Step 4: constructing a mathematical processing quality model of a hybrid flow shop. [0079] Regarding a continuous processing with variable parameters in the hybrid flow shop model, a continuous processing is implemented by setting the adjustment time as a variable parameter. In an actual production, a continuous processing such as heat treatment mainly is implemented mainly through a heating furnace apparatus, the adjustment time is the heating and holding time of the workpiece which directly reflects the processing quality of the workpiece. In the actual processing, the holding time is a numerical value within a range under process requirements, and the optimal holding time is a value between the minimum holding time and the maximum holding time. To ensure the best quality of the workpiece after heating, an optimal holding time gap value is set within a holding time range under process requirements, to optimize the holding time gap and thus improve the heating quality of forgings. The optimal holding time gap value being expressed as: [0080] hgT" (tiro -hT"ll)* (1-D,)1 (11).
[0081] By calculating a mean square error of an actual scheduling holding time and an optimal holding time, the difference between the actual holding time and the optimal holding time of the workpiece is reflected, and a sum of mean square errors of optimal holding time gaps of all workpieces is established to construct the following quality model in hybrid production: 1 17 2 [0082] , -11TH *(1- (12).
n * h,=, Step 5: constructing a multi-objective function of a hybrid flow shop scheduling model.
[0083] Aiming at the completion time model and the quality model of the hybrid flow shop scheduling model for continuous processing with variable parameters and intermittent processing with variable parameters, a multi-objective scheduling optimization model is established, so as to perform scheduling optimization from efficiency and quality both, in which the efficiency is reflected by the completion time, and the quality is reflected by the optimal holding time gap. A multi-objective optimization equation established is described as follows: f =min(T,Q) (13) T = max [ (T; (i =1,2,3,* * *, n) J-1 +" * Du_i)+Ty" +TT +T"") (14) h -DJ)] Ez[OpTv-hpr:y.(l Q = s.t.
Ty' =t "-st" (15) =rt" -lig (16) am <mit] tt" (17) et"5.rt" (18) et?, = (19) et u= st4,±0=tt,(,+,) (Di =0) (20) wto (pH = o) (21) sut = la; -Dj)+ 1.1 (22) hry-s hTv shirr (23).
[0084] The symbols used in the mathematical model are as follows: Symbol Definition Number of workpieces Serial number of each workpiece, i = I, 2, Number of processing stages Serial number of each processing stage, j= 1, 2, m Serial number of a workpiece previous to workpiece i on the same manufacturing apparatus Serial number of a workpiece previous to workpiece i on the same transport apparatus 0 indicates that processing stage] is a continuous processing; Di= 1 indicates that processing j is an intermittent processing Quantity of a continuous production processes across the whole production line Maximum value of completion time Waiting time before transport of workpiece i in processing stage] Transport time of workpiece i in processing stage] Tv' Waiting time before processing of workpiece i in processing stage] Teir Preparation time of workpiece i in processing stage] Tf; Processing time of workpiece i in processing stage] 77 Adjustment time of workpiece i in processing stage] Time gap between the manufacturing of the workpiece i and the previous workpiece on the same manufacturing apparatus in processing stage] Time gap between the transporting of the workpiece i and the previous workpiece on the same transport apparatus in processing stage] Start time moment of workpiece i in processing stage] ti,, Transport start time moment of workpiece fin processing stage] Start time moment of waiting time before processing of workpiece i in processing stage] rto Start time moment of preparation time of workpiece i in processing stage] Start time moment of processing time of workpiece i in processing stage] sut" Start time moment of adjustment time of workpiece i in processing stage] etlf End time moment of workpiece i in processing stage] Adjustment time of workpiece i in processing stage j, when the processing apparatus is a machining apparatus hT" Heating and holding time of workpiece tin processing stage] h77" Allowable maximum value of heating and holding time of workpiece i in processing stage] 11.
hrt7in hff; Allowable minimum value of heating and holding time of workpiece i in processing stage] Optimal heating and holding time of workpiece i in processing stage] hgT, Absolute difference between actual heating and holding time period and optimal heating and holding time of workpiece i in processing stage] hgTmsE Mean square error between actual heating and holding time period and optimal heating and holding time of workpiece i in processing stage j

Claims (1)

  1. WHAT IS CLAIMED IS: 1. A scheduling method for a hybrid flow shop featuring continuous processing and intermittent processing with a variable parameter, comprising following steps: Si, building a time relationship network of wo rkpieces/man ufactu ring apparatuses/transport apparatuses, wherein time factors related to each workpiece comprise: a waiting time before transport a transport time r, a waiting time before processing Psi', a preparation time r, a processing time P9, and an adjustment time I, wherein when a processing stage is the continuous processing with the variable parameter, the waiting time before transport and waiting time before processing at a latter processing stage are both zero, and the variable parameter is an adjustment time of this stage and when the processing stage is the intermittent processing, the waiting time is able to be adjusted to make a scheduling plan reasonably; time factors related to processing apparatus comprise: a processing apparatus gap time a preparation time Tr, a processing time TP, and an adjustment time r; and time factors related to transport apparatus comprise: a transport apparatus gap time r and a preparation time r; 52, constructing a completion time model of a hybrid flow shop, wherein there are two processing stages in the hybrid flow shop: a continuous processing with a variable parameter and an intermittent processing with a variable parameter, the constructed mathematical completion time model is as follows: = mav (7' * 13(i_o +7;1 +77 * Do_)+rr + +) (i = 1, 2,3,. * * ,n) (1) /-s.t.Ty' = 11, -st, (2) Ty"P = rt u -ttu (3) tty, < wt" tto (4) el,, rt (5) el,, = xi _i) (6) et, =stiii+0=t1,041) (D, =0) (7) wt,. =11"(Di, =0) (8) T"s =et,/ -su 1 u =hT * (I -D,)+ eT: .Di (9) hT",""" s hT" 5 hTr (10) wherein equation (1) denotes the mathematical model targeting completion time, and equations (2)-(10) denote constraint conditions; wherein, equation (2) denotes a constraint of variable waiting time before transport, equation (3) denotes a constraint of variable waiting time before processing, equation (4) denotes a constraint of a sequential relationship between two adjacent workpieces on the same transport apparatus, equation (5) denotes a constraint of a sequential relationship between two adjacent workpieces on the same manufacturing apparatus, equation (6) denotes a relationship between two processing stages of the same workpiece, equation (7) denotes a relationship between two production processes for a same workpiece before transport when the previous processing stage is continuous processing, equation (8) denotes a relationship between two production processes for a same workpiece after transport when the previous processing stage is continuous processing, equation (9) denotes a definition of adjustment time for each of different processing stages, and equation (10) denotes a constraint of the variable adjustment time between maximum and minimum values; S3, constructing a processing quality model of a hybrid flow shop, wherein regarding a continuous processing with the variable parameter, the continuous processing is realized by setting the adjustment time as the variable parameter, in an actual production, the continuous processing such as heat treatment is implemented mainly through a heating furnace apparatus, the adjustment time as the variable parameter is a heating and holding time of the workpiece, which directly reflects the processing quality of the workpiece, and in the actual processing, the holding time is a numerical value within a range under process requirements, and an optimal holding time is a value between a minimum holding time and a maximum holding time, in order to ensure a best quality of the workpiece after heating, a value of an optimal holding time gap is set within a holding time range under process requirements, to optimize the holding time gap and thus improve the heating quality of the workpiece; wherein the value of the optimal holding time gap is expressed as: hgl; = (111;, -h1;i8)* (1-D,)1 (I I) by calculating a mean square error of an actual scheduling holding time and an optimal holding time, a difference between the actual holding time and the optimal holding time of the workpiece is reflected, and a sum of mean square errors of optimal holding time gaps of all workpieces is established to construct following processing quality model in hybrid production: " hg7;, =-11[(hT -hT,B) ( -2 * D.,)] (12) n h " S4, constructing a multi-objective function of a hybrid flow shop scheduling model, wherein aiming at the completion time model and the quality model of the hybrid flow shop scheduling model featuring continuous processing and intermittent processing with variable parameters, a multi-objective scheduling optimization model is established to perform scheduling optimization from efficiency and quality both; wherein the efficiency is reflected by the completion time, and the quality is reflected by the optimal holding time gap, a multi-objective optimization equation established is described as follows: f = min(T,Q) (i= 1, 2,3, * * * , n) (13) s.t. A' (14) T = max E(Tuin, Du j) + Ti +T,7 * D(1_,)+Tt," + T,I 7; ) (15) [ 14 (16) 1 n h r (17) (18) (19) (20) (21) (22) (23) DJ)] Q = ZEIPIPT,l -hPTIJR)2 * nh = tt" -St, = rty -ttg tt < wry, et,/ S r111 el = st,(J-1) et, = stio,o= ft(i_o (1), =0) wry = rtfi (D = 0) 7;1 = et" -so,. =h1 -(1-D + e71; Di hT"'"" < hT" the symbols used in the equation are detailed as follows: Symbol Definition Number of workpieces Serial number of each workpiece, i = 1, 2, ..., n in Number of processing stages Serial number of each processing stage,] = 1, 2, ...Serial number of a workpiece previous to workpiece i on the same manufacturing apparatus Serial number of a workpiece previous to workpiece i on the same transport apparatus D, = 0 indicates that processing stage j is a continuous processing; D, = 1 indicates that processing stage] is an intermittent processing Number of continuous processing stages across the whole production line Gun Maximum completion time To"' Waiting time before transport of workpiece i in processing stage] Tor. Transport time of workpiece i in processing stage j Waiting time before processing of workpiece i in processing stage] Tyr Preparation time of workpiece i in processing stage/ Tr, Processing time of workpiece i in processing stage] TJ Adjustment time of workpiece i in processing stage] Gap time between manufacturing of the workpiece i and the previous workpiece on the same manufacturing apparatus in processing stage] Gap time between transporting of the workpiece i and the previous workpiece on the same transport apparatus in processing stage] sr, Stan time moment of workpiece i in processing stage j Transport start time moment of workpiece i in processing stage] Start time moment of waiting time before processing of workpiece i in processing stage] rtii Stan time moment of preparation time of workpiece i in processing stage] pt Processing start time moment of workpiece i in processing stage j sut,, Start time moment of adjustment time of workpiece i in processing stage j el,/ End time moment of workpiece i in processing stage] Adjustment time of workpiece i in processing stage j, when the processing apparatus is a eI machining apparatus hTii Heating and holding time of workpiece i in processing stage] Allowable maximum value of heating and holding time of workpiece i in processing stage hrmtn Allowable minimum value of heating and holding time of workpiece i in processing stage] Optimal heating and holding time of workpiece i in processing stage] Absolute difference between actual heating and holding time and optimal heating and holding hgru time of workpiece i in processing stage] Mean square error between actual heating and holding time and optimal heating and holding time hgrmsk of workpiece i in processing stage 2. The scheduling method for a hybrid flow shop featuring continuous processing and intermittent processing with variable parameters according to claim 1, wherein essential requirements of the scheduling method are as follows: 1) composition: a raw material storage area, a finished product storage area. m processing stages (rn>2); (m-b) transport stages; 2) each of the processing stages adopting one or more identical manufacturing apparatus; 3) each of the transport stages adopting one or more identical transport apparatus, and each transport stage usually adopting one transport apparatus due to a limited transport space; 4) in the manufacturing process, n jobs. m processing stages for processing, and (m+1) transport stages for transporting being involved; 5) each manufacturing apparatus only handling one job at a time; 6) each transport apparatus only transporting one job at a time; 7) each workpiece only be handled by one manufacturing apparatus or one transport apparatus at a time; 8) the processing stage mainly consisting of two types of processing: the continuous processing with the variable parameter, and the intermittent processing with the variable parameter; 9) in the continuous processing stage with the variable parameter, it being required that when processing is about to be completed in this stage, there is a variable parameter within a domain of definition [c, d], and this parameter is adjusted in the scheduling plan to ensure that a variety of hybrid processing parts are able to be arranged reasonably to be processed; and 10) in the intermittent processing stage with the variable parameter, it being required that when processing is completed in this stage, waiting time before transport and waiting time before processing in the next stage are adjusted to ensure reasonable and efficient production scheduling, and the waiting time being adjusted within a domain of definition [0, +op].
GB2208781.1A 2019-11-26 2020-10-27 Method for scheduling hybrid flow shop comprising variable parameter continuous processing and intermittent processing Pending GB2610032A (en)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
CN201911175486.1A CN110825056B (en) 2019-11-26 2019-11-26 Hybrid flow shop scheduling method with variable parameter continuous processing and intermittent processing
PCT/CN2020/123789 WO2021103891A1 (en) 2019-11-26 2020-10-27 Method for scheduling hybrid flow shop comprising variable parameter continuous processing and intermittent processing

Publications (2)

Publication Number Publication Date
GB202208781D0 GB202208781D0 (en) 2022-07-27
GB2610032A true GB2610032A (en) 2023-02-22

Family

ID=69559540

Family Applications (1)

Application Number Title Priority Date Filing Date
GB2208781.1A Pending GB2610032A (en) 2019-11-26 2020-10-27 Method for scheduling hybrid flow shop comprising variable parameter continuous processing and intermittent processing

Country Status (4)

Country Link
JP (1) JP2022504393A (en)
CN (1) CN110825056B (en)
GB (1) GB2610032A (en)
WO (1) WO2021103891A1 (en)

Families Citing this family (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN110825056B (en) * 2019-11-26 2020-12-04 北京工业大学 Hybrid flow shop scheduling method with variable parameter continuous processing and intermittent processing
CN111932105B (en) * 2020-08-05 2024-02-06 万华化学(宁波)有限公司 Intermittent chemical product scheduling method, storage medium and system
CN113341896B (en) * 2021-06-07 2022-08-05 电子科技大学 Discrete manufacturing-oriented dynamic integrated workshop scheduling and assembly sequence planning method
CN113741369B (en) * 2021-09-07 2023-04-21 福州大学 Mixed flow shop scheduling optimization method
CN114066065B (en) * 2021-11-18 2024-07-12 福州大学 Multi-target mixed zero-idle replacement flow shop scheduling method and system

Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2000271839A (en) * 1999-03-25 2000-10-03 Nippon Telegr & Teleph Corp <Ntt> Flow shop scheduling device, flow shop scheduling method, and storage media for program solving flow shop scheduling
US20050154625A1 (en) * 2004-01-14 2005-07-14 Agency For Science, Technology And Research Finite capacity scheduling using job prioritization and machine selection
CN101609334A (en) * 2009-07-13 2009-12-23 浙江工业大学 Job shop multi-process routes in batches method for dynamically re-dispatching based on the two-stage differential evolution algorithm
CN105700495A (en) * 2016-01-13 2016-06-22 济南大学 Flexible job shop scheduling machine selection method based on processing time grade
CN108803531A (en) * 2018-07-17 2018-11-13 浙江大学 Closed-loop system process monitoring method based on sound feature Cooperative Analysis and orderly Time segments division
CN109918771A (en) * 2019-03-05 2019-06-21 北京工业大学 The energy-saving distribution model of hybrid flow forge under a kind of more time factors
CN110825056A (en) * 2019-11-26 2020-02-21 北京工业大学 Hybrid flow shop scheduling method with variable parameter continuous processing and intermittent processing

Family Cites Families (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP3317144B2 (en) * 1996-06-11 2002-08-26 新日本製鐵株式会社 Integrated manufacturing design processing system
JPH10118896A (en) * 1996-10-18 1998-05-12 Kanegafuchi Chem Ind Co Ltd Schedule preparation support system
JP4734024B2 (en) * 2005-05-12 2011-07-27 新日本製鐵株式会社 Hot rolling mill heating / rolling schedule creation apparatus, creation method, computer program, and computer-readable recording medium
JP2007061870A (en) * 2005-08-31 2007-03-15 Nippon Steel Corp Device and method for preparing rolling schedule, computer program and computer readable storage medium
JP4932294B2 (en) * 2006-03-23 2012-05-16 新日本製鐵株式会社 Manufacturing specification determination support system, manufacturing specification determination support method, computer program, and computer-readable recording medium
CN104376424B (en) * 2014-11-27 2017-07-11 东北大学 A kind of many producing line coil of strip coordinated scheduling methods in cold rolling area of iron and steel enterprise
CN105483310B (en) * 2015-11-23 2017-05-10 东北大学 Steelmaking batch grouping and production scheduling method for whole process production
CN108469798A (en) * 2018-05-15 2018-08-31 哈尔滨理工大学 A kind of Job-Shop system based on line side library feeding

Patent Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2000271839A (en) * 1999-03-25 2000-10-03 Nippon Telegr & Teleph Corp <Ntt> Flow shop scheduling device, flow shop scheduling method, and storage media for program solving flow shop scheduling
US20050154625A1 (en) * 2004-01-14 2005-07-14 Agency For Science, Technology And Research Finite capacity scheduling using job prioritization and machine selection
CN101609334A (en) * 2009-07-13 2009-12-23 浙江工业大学 Job shop multi-process routes in batches method for dynamically re-dispatching based on the two-stage differential evolution algorithm
CN105700495A (en) * 2016-01-13 2016-06-22 济南大学 Flexible job shop scheduling machine selection method based on processing time grade
CN108803531A (en) * 2018-07-17 2018-11-13 浙江大学 Closed-loop system process monitoring method based on sound feature Cooperative Analysis and orderly Time segments division
CN109918771A (en) * 2019-03-05 2019-06-21 北京工业大学 The energy-saving distribution model of hybrid flow forge under a kind of more time factors
CN110825056A (en) * 2019-11-26 2020-02-21 北京工业大学 Hybrid flow shop scheduling method with variable parameter continuous processing and intermittent processing

Also Published As

Publication number Publication date
WO2021103891A1 (en) 2021-06-03
CN110825056B (en) 2020-12-04
CN110825056A (en) 2020-02-21
GB202208781D0 (en) 2022-07-27
JP2022504393A (en) 2022-01-13

Similar Documents

Publication Publication Date Title
GB2610032A (en) Method for scheduling hybrid flow shop comprising variable parameter continuous processing and intermittent processing
CN109918771B (en) Energy-saving scheduling model of mixed flow forging workshop under multiple time factors
CN106078090B (en) A kind of forging technology of large axis forging
MX2023003559A (en) Glass manufacturing apparatus and method.
AU2020200077B2 (en) Support frame
JP2013102041A5 (en)
CN104388851A (en) Machining deformation process control method for aluminum alloy multi-frame plate part
CN103801499A (en) Multi-station multicolor hardware product spray coating method and equipment
TWI626094B (en) Method for controlling temperatures of a heating furnace
CN113151666A (en) Operation control method, device and system for continuous vacuum heat treatment furnace
CN109112466A (en) Plasma spraying Ni Superalloy Coating high throughput preparation method
KR101785473B1 (en) Cooling water manifold manufacturing method for cooling mold
CN106111879A (en) A kind of moulding process of fuel injector nozzle
JP2006524767A (en) Method for maintenance work of a gas turbine
Sosiady Meningkatkan Kinerja Karyawan dengan Kecerdasan Emosional dan Kemampuan Kerja di Kota Dumai
JP7162996B1 (en) Heat treatment equipment
CN219674720U (en) Quick heating device of battery
CN106495743B (en) The preparation method of ceramic fingerprint piece preprocess method and ceramic fingerprint piece
WO2014006702A1 (en) Control device and control method for thick plate multi-rolling
MX2021007952A (en) In line, continuous proppant coating method.
CN207238326U (en) A kind of afterbody clamping tooling of fuel tank UV sprayings
CN114156872B (en) Intelligent current distribution method
CN117505752A (en) Streamline control method for large-size titanium alloy rod-shaped special-shaped section forging
CN106078119A (en) A kind of moulding process of fuel injector
CN112684832B (en) Method and equipment for overcoming temperature reaction lag of silicon carbide annular carrier