Journal of Software - Academy Publisher

08.12.2012 Views
802 JOURNAL OF SOFTWARE, VOL. 6, NO. 5, MAY 2011 Resource Agent Management Agent Find new time Y Workpiece Agent Release order Y Scheduling released order Planned order Emergency order Report Emergency scheduling order N N Stop jobs Other Agent Malfunction Notice Workpiece Agent feedback Resource Agent record Recycling order Process failure order IV. BASIC SCHEDULING ALGORITHMS IN AGENT The dynamic re-scheduling based on MAS composes of local scheduling by a multi-stage process. The local scheduling of each stage is carried out based on CNP model, the basic algorithm is as follows: Step 1 Scheduling information received from the outside world after the initial Management Agent release price PR i . It can be defined: PRi = ( ti Ta Ba Ma) t i Means that other Agent where the deadline to respond Ta means that the time required to complete the task constraints, Ba means space constraints, M a means material constraints. Then for emergency insertion of the work piece, once the original work piece delay, the delay time should to be as short as possible, so the time constraint can be expressed as: Ta = min[( Ts + ti),( Td + Tp)] (10) S.t. cik − pik + M(1 −aihk ) ≥ cih , i = 1,2,... n; h, k = 1,2,... m cjk − cik + M(1 −xijk ) ≥ pjk , i, j = 1,2,... n; k = 1,2,... m cik ≥ 0 , i = 1, 2,... n; k = 1, 2,... m find Y Planned order Figure6. Dynamic scheduling flow chart © 2011 ACADEMY PUBLISHER N Workpiece Agent Recover task Material shortage feedback Management Agent Y Planned Order N Other Agent x ijk =0 or 1, i, j = 1,2,... n; k = 1,2,... m In which (10) indicates time constraints. s T means the time that Management Agent make the initial offer, Td means the latest time that jobs end, p T means the average of extend operating time, which ik c and ik p mean that the finished time and the processing time of work piece i and machine k . aihk and xijk are coefficient and the indicator variable indicating. Step 2 Equipment Agent tender offer are given counter offer, Equipment Agent first assess their own parts to meet the resource constraints, and then give counter offer PRj = ( aj Tc, Mc) , a j means the commitment wait time, Tc means the first beginning time that is produced by the Equipment Agent which after assess, if the Equipment Agent do not meet a T , a B , M a ,or occupied by either the state constraints, then give up bidding. If T c is idle, then the Equipment Agent initiate to Resource Agent for counter-bids which is in the idle time scheduling, to save the scheduling time. Step 3 Resource Agent assesses the counter offer and then authorize. Management Agent evaluates all bids which returned, according to the formula: min[( Tc + Tp), Mc] .Select the best Equipment Agent to authorize, that is, considering the earliest start time of the Equipment Agent, the workpiece capacity and efficiency. Step 4 Perform an operation process. The Equipment Agent authorizes to perform job tasks, in the process of failure may occur. If normal, while the Management Agent of total consumption statistics, and then back to the Equipment Agent. If failure occurs, report to the Supervision Agent, to stop the operation and into the fault repair process of negotiation. V. SIMULATION RESULTS For example, to a machine shop, considering the equipment of 5parts, 4processes and 8machines; the workshop is to complete planning, milling, turning, drilling and other processes. There are two multifunctional machines: two different specifications of the plan and two specifications different lathe, a milling machine and a multi-function machine tool. Relationship between process machines is shown in Table I(in the table, 1 indicates that the machine can complete the process, 0 not).Process sets of the workpiece are shown in Table II. The processing time is shown in Table III. Consider two cases, one piece of the delivery is not particularly tense situation, is set to FIFO scheduling the delivery of products under the rules of the average processing cycle, the other is a more intense delivery time, that is 1:1.2. MAS proposed methods will be used in the FIFO rules and EDD rules performance comparison, the simulation results are shown in Table IV.

JOURNAL OF SOFTWARE, VOL. 6, NO. 5, MAY 2011 803 ID Machine Process As can be seen from the table IV, Fig.7 and Fig.8(G- FIFO means General FIFO;G-EDD means General EDD;G-MAS means General MAS;E-FIFO means Emergency FIFO;E-MAS means Emergency MAS;G-F- FIFO means General Failure FIFO;G-F-MAS means General Failure MAS;E-F-FIFO means Emergency Failure FIFO;E-F-MAS means Emergency Failure MAS), using the proposed consultation mechanism from this paper, for reducing the weighted average delay in delivery of products, improve product time delivery, has an extremely effective results. For the problem of equipment failure, assuming a daily equipment failure 12h, simulation time for one TABLE II. EQUIPMENT AND PROCESS Piece ID number 1 procedure 2 procedure 3 procedure 4 procedure j1 Plane(id:1) Milling (id:2) Diamond (id:4) Car (id:3) j2 Car (id:3) Diamond (id:4) Milling (id:2) Plane (id:1) j3 Milling (id:2) Plane (id:1) Car (id:3) Diamond (id:4) j4 Diamond (id:4) Plane (id:1) Milling (id:2) Car (id:3) j5 Milling (id:2) Diamond (id:4) Plane (id:1) Car (id:3) TABLE III. PROCEDURE PROCESSING TIME Machine Plane Milling Car Diamond A B C C G D E F H j1 3 4 6 10 8 2 3 5 9 j2 7 8 8 5 6 6 7 6 4 j3 2 3 3 3 5 4 5 3 3 j4 8 9 9 2 7 11 12 7 7 j5 3 5 6 5 3 5 6 8 6 TABLE IV. MODEL SIMULATION RESULTS Production Line Scheduling Time delivery/% Weighted average delay/h Status rules A B C D E F G H A B C D E F G H FIFO 49 48 51 57 50 50 50 51 21 18 18 16 16 20 15 16 General EDD 46 54 55 61 65 50 52 68 MAS 85 91 94 88 90 84 93 80 3 3 1 1 8 7 9 8 Emergency FIFO 0 0 0 0 0 0 0 0 55 84 65 59 71 65 84 74 MAS 100 94 85 89 98 89 92 94 5 7 5 3 10 6 8 6 Production Line Status A(Planer1) B(Planer2) Scheduling rules TABLE I. RELATIONSHIP BETWEEN THE MACHINE AND PROCESS C(Milling) D(Lathe1) E(Lathe2) TABLE V. EQUIPMENT FAILURE MODEL SIMULATION F(Multifunction) G(Lathe) H(Multifunction) P1 1 1 0 1 0 1 1 0 P2 0 0 1 0 0 0 0 1 P3 0 0 0 1 1 0 1 0 P4 0 0 1 0 0 1 1 0 Time delivery /% Weighted average delay /h A B C D E F G H A B C D E F G H General Failure FIFO 55 58 51 55 54 59 50 49 41 20 15 17 19 21 19 20 MAS 96 92 92 95 90 95 99 94 6 8 3 3 7 6 4 5 Emergency FIFO 0 0 0 0 0 0 0 0 35 33 24 32 29 16 31 121 Failure MAS 99 94 88 89 98 89 92 94 8 6 6 11 11 8 7 8 © 2011 ACADEMY PUBLISHER month, the same as the other set, FIFO is not processed on equipment failure, MAS consultation mechanism with self-processing, simulation statistics are shown in Table V, Fig.9 and Fig. 10. Fault simulation shows that the proposed consultation mechanism of local autonomy which reduce equipment failures better impact on the production line. In the normal fault and the fault of the emergency, were increased on-time delivery rate, and reduce the average weighted delay.

Page 1 and 2: Journal of Software ISSN 1796-217X

Page 3 and 4: JOURNAL OF SOFTWARE, VOL. 6, NO. 5,



























Page 57: JOURNAL OF SOFTWARE, VOL. 6, NO. 5,








Page 82 and 83: 826 JOURNAL OF SOFTWARE, VOL. 6, NO






























































Page 207 and 208: Aims and Scope. Call for Papers and

system

software

based

model

method

knowledge

information

process

algorithm

fault

journal

academy

publisher

www.academypublisher.com

Journal of Software - Academy Publisher

Journal of Software - Academy Publisher ... View more Journal of Software - Academy Publisher

Delete template?

Save as template ?

Journal of Software - Academy Publisher Journal of Software - Academy Publisher