CN101763100A - Production optimization system based on dual-progress factor and optimization method thereof - Google Patents

Abstract

The invention discloses a production optimization system based on a dual-progress factor and an optimization method thereof. The system comprises a data collecting module, a production efficiency curve chart analysis module and a data feedback control module, wherein the data collecting module is used for collecting initial data used for calculating work efficiency, and the production efficiency curve chart analysis module comprises a work load conversion part, a curve plotting part and a curve display part. The optimization method comprises a data collecting stage, a production efficiency curve analysis stage and a data feedback control stage. The invention provides a common feedback control method suitable for a task parallel model, a task dependence model and a task combination model on the basis of combing task progress and time progress and can improve the efficiency of the whole assembly line by an optimal means to enable the original uncontrollable assembly line production rate to become the definitely controllable assembly line production rate, thereby greatly improving the productivity.

Description

A kind of production optimization system and optimization method thereof based on dual-progress factor

Technical field

The present invention relates to a kind of optimization system and optimization method thereof of production, be based on the optimization system and the optimization method thereof of the production of dual-progress factor in particular.

Background technology

At various production fields, a task can resolve into a plurality of subtasks usually, generally has following several restriction relation (model) between these subtasks:

1) concurrent execution: if working group is made up of A, B two people, A and B start working simultaneously, and A and B do not influence mutually, and A, B all finish, and then whole project is finished.If A finishes earlier, B does not also finish, and A can participate in the work of B at once.

2) serial is carried out, and has dependence, as: subtask A finishes back B and can begin

3) combination is carried out: task A is the combination of a1, a2, and any one that this means a1, a2 begins promptly to represent the beginning of A; And a1 and a2 just can regard as A and finish when finishing.

For ease of the control progress, reasonably the allocation schedule resource needed to make the plan before task is carried out.Plan comprises: the expectation of task (and each subtask) begins concluding time, workload, distribute to which personnel does or the like, in the actual task implementation, by monitoring period progress, completed workload, in time make judgement: inadequate resource is delayed, whether existed to task whether, so that pinpoint the problems risk as soon as possible, to remodify plan, guarantee that task is guaranteed the quality on schedule to finish.

The ultimate principle of prior art:

Ask the current time progress: (general ActualTimeBegin==PlanTimeBegin)

Time_Progress＝(Now-ActualTimeBegin)/PlanDateRange＊100％

PlanDateRange:＝[PlanDateBegin，PlanDateEnd]＝(PlanDateEnd-PlanDateBegin+1)

Wherein, 0＜=Actual_Time_Progress＜=100% when the formula value of calculating goes beyond the scope, uses boundary value.

(2) ask the current task progress: (workload with chronomere (hour) calculated, January=22.5 days 1 day=6 hours)

Task_Progress＝Sum(DayCostPerMan＊

TaskAllocatedManNum){ActualTimeBegin..Now}

/PlanTaskTotalCostNeeded＊100％

Wherein, 0＜=Task_Progress＜=100% when the formula value of calculating goes beyond the scope, uses boundary value.

If Task Progress＞=time schedule, the explanation project make good progress; Otherwise then there is the risk of delaying in explanation, and need investigate a matter out as early as possible aspect what.

Based on WBS (work breakdown structure):.

The realization that above technology has only is confined to Task Progress, time schedule, that have even consider model discretely, its estimation is too coarse, can not find internal association between the two, thereby whole task is in the implementation of reality, granularity lacks refinement, has also ignored individual difference on task execution efficient.On people's machine production line, use the control from view of profit and the optimization of existing techniques in realizing, locate and pinpoint the problems slowly, be unfavorable for improving fast the efficient of people's machine production line.

Summary of the invention

1, invents the technical matters that will solve

For overcoming the shortcoming of above-mentioned prior art, the invention provides a kind of optimization system and optimization method thereof of the production based on dual-progress factor, production line field at man-machine compounding practice, feedback task efficient and monitor task progress, be applicable to the Control and Feedback algorithm under the multiple model of tasks in parallel, dependence, combination, and generate progress, efficient feedback form automatically according to statistics.Carry out the parameter tuning by feedback data, weigh the work efficiency of individuality, group comparatively, so that can formulate the purpose of reaching adjustment, optimal combination in personnel placement, plan better.

2, technical scheme

Technical scheme of the present invention is as follows:

A kind of production optimization system based on dual-progress factor, form by data collection module, production efficiency curve map analysis module and data feedback control module, the collection of the raw data that is used for evaluation work efficient wherein, production efficiency tracing analysis module is made up of workload conversion, curve plotting and curve display three parts.

Above-mentioned data collection module is made up of a set of counters.Native system is as the basis of realizing with people's machine production line production system.

A kind of production optimization method based on dual-progress factor the steps include:

(1) data aggregation: finished by data collection module, data collection module is made up of a set of counters, and the unit interval of counter image data is Δ t, the unit interval of representative from the t1 time to the t2 time.Each stream line operation personnel is a role in counter module, and counter is whenever collecting the work that the role finishes in Δ t, and counter will add 1, all working amount that counter can be added up each role respectively and finished;

(2) production efficiency tracing analysis: comprise workload conversion, curve plotting, curve display three steps composition, first step: workload converts: at first, set baseline value, establish: $\mathrm{\Γ}=\frac{W}{T}=1$

Wherein, W is the real work efficient time; T is the schedule work efficient time.

T=n Δ t plan T in the time amount of finishing the work be X;

Second portion: tracing analysis:

Step1: with running time and the ratio of schedule work time is the longitudinal axis, promptly is the longitudinal axis with Γ; Time shaft is a transverse axis;

Step2: datum line be free in one of Γ=1 curve with transverse axis, the work efficiency time that obtains in the Δ t time is sampled point, will become the running time curve after the connection of neighbouring sample point;

Step3: the sampled point computing method are: $\mathrm{\Γ}=\frac{E_{t_0}}{T},E_{t_0}$ Calculating because the difference of production models is divided into dual mode;

Model one: when production models are concurrent execution,

Computing formula as follows:

$E_{t_0}=\frac{\underset{i=1}{\overset{N}{\mathrm{\Σ}}}\underset{t=t_0-\frac{W}{2}}{\overset{t_0+\frac{W}{2}}{\mathrm{\Σ}}}{\mathrm{Workload}}_{M_i,t}}{N*{\mathrm{WorkBase}}_W}$

Get a fixing moving window size W during calculating;

Model two: when production models are that serial is carried out or combination is carried out constantly,

Computing formula as follows:

$E_{t_0}=\frac{\underset{i=1}{\overset{N}{\mathrm{\Σ}}}\underset{t_0}{\overset{0}{\mathrm{\Σ}}}{\mathrm{Workload}}_{M_i,t}}{N*{\mathrm{WorkBase}}_W}$

Γ ' ₁Deviate=| Γ ' ₁-Γ |

(3) data FEEDBACK CONTROL:

Step1: calculation deviation value.Under the normal condition, calculate

Value should represent work efficiency stable good, otherwise the state representative be unusual near horizontal reference value 1.0.

Abnormal conditions are as follows in the step (3):

First kind: continuous coverage in a period of time, find

It is bigger to fluctuate: this illustrates unstable working condition, can illustrate generally what problem has appearred in individual working condition, needs on-the-spot investigation reason; The measurement of stability bandwidth D:

If time range [t ₁, t ₂], then the fluctuation of the production efficiency in this segment limit D can weigh with following formula:

${D_{[t_1,t_2]}}^2=\frac{\underset{t=t_1}{\overset{t_2}{\mathrm{\Σ}}}{(E_t-1)}^2}{(t_2-t_1)/\mathrm{\Δt}}$

Second kind: continuous coverage in a period of time, find Departed from 1.0 (higher or on the low side) in general, then can illustrate: the low or organizer and governor of the too high situation two of individual productivity, individual productivity need adjust the WorkBase of a drag _WReference value (the reference value value has reflected the ability level of whole tissue).

Above step realizes in interactive mode.

3, beneficial effect

The invention provides optimization system and optimization method thereof by a kind of production of dual-progress factor, combine on the basis of Task Progress and time schedule, proposed to be applicable to the general Control and Feedback method of tasks in parallel, dependence, built-up pattern, the data of system feedback can reflect the problem of concrete link effectively, and judgement by deviation ratio, concrete link is investigated and adjusted, can improve the efficient of whole piece streamline with optimized means.The following feedback monitoring that can continue has been carried out continuous optimization to streamline, makes original uncontrollable streamline throughput rate, has become controlled, clear and definite control, has improved yield-power greatly.

Description of drawings

Fig. 1 is a basic structure synoptic diagram of the present invention.

Embodiment

Further specify the present invention by the following examples.

Embodiment 1

Embodiment 1

Certain company is engaged in the assembling of display apparatus.The human-machine operation pipeline system is the dependence model in the production models.

Before not introducing the present invention.When the display assembling yield-power of the integral body of the said firm descends, can only assess from the Task Progress or the time schedule of the overall output of streamline, can't carry out the refinement assessment to each operator of each link on the streamline, the difficulty that causes increasing productivity is big.

Introduce after the present invention, the throughput rate situation of each link in the feedback flow waterline in real time, and in time provide the standard of adjusting each link on the streamline according to departure, and each operation human efficiency can be calculated and need improve and improved efficiency value by the baseline deviometer, can promptly locate the low problem points of pipeline efficiency, thereby improve and improve the yield-power of whole piece production line.

According to the present invention, the said firm at first carries out the installation data harvester to each link that relates to human-machine operation on the streamline, and everyone machine operation process is carried out tracing and monitoring and data acquisition.Analyze data and collect the system that finally enters into by the sensing device on the streamline.The work of data acquisition is mainly carried out around production time, production efficiency.

Set the baseline and the deviation range value of different links on the streamline.It is following flow process that the concrete streamline of the said firm has man-machine participation link: be divided into and be four processes: electric welding link, plug wire link, assembling link, debugging link.

Each link is set reference point

Link	Schedule work efficient time T	The scope of stability bandwidth D	Explanation
				Electric welding	7	≤ 3 ‰	Because the electric welding stage requires the property finished higher.Therefore offset ranges is little
Plug wire	6	≤ 5 ‰
				Debugging	6.5	≤ 5 ‰
Assembling	7.5	≤ 7 ‰	Because assembling stage influence factor is a lot, increased the uncertainty of work, offset ranges is big slightly

Equal installation data collection module in these links, and unification feeds back to the production efficiency curve map with image data, the stability bandwidth that shows according to different links compares with plan stability bandwidth scope, analyze again, find out and make the off-limits reason of stability bandwidth rate, constantly be optimized, reach the raising of streamline yield-power.

In following formula calculates, fixing moving window size W=1 days, t ₀Be some effective working days, below give tacit consent to the working cell of being got and be 3.

Below how we carry out to the assembly production chain of display apparatus that Control and Feedback and implementation efficiency optimize.

1, electric welding link sampling statistics:

T=7 in the electric welding link.

During electric welding, there are two workmans concurrent, are concurrent execution model, calculate according to model one in production line work

At sampled point t ₁The time, $E_{t_1}=\frac{\underset{i=1}{\overset{3}{\mathrm{\Σ}}}\underset{t=t_1-\frac{1}{2}}{\overset{t_1+\frac{1}{2}}{\mathrm{\Σ}}}{\mathrm{Workload}}_{M_i,t}}{3*{\mathrm{WorkBase}}_1}=7.01$

${\mathrm{\Γ}}_1^{\′}=\frac{W}{E_{t_1}}=\frac{7.01}{7}=1.001$

Deviate 1=| Γ ' ₁-Γ |=| 1.00-1|=0.001

Deviation ratio 1=1 ‰

Other sampled points, same t ₁Computing formula, can add up obtaining following table:

Stability bandwidth is analyzed:

Actual stability bandwidth

At sampling number according to interior stability bandwidth less than≤3 ‰, so electric welding link working efficiency situation is good.

2, plug wire link sampling statistics:

T=6 in the plug wire link.

During plug wire, two workman's serials are arranged, be the serial model, calculate according to model two in production line work At sampled point t ₁The time, $E_{t_1}=\frac{\underset{i=1}{\overset{N}{\mathrm{\Σ}}}\underset{t_0}{\overset{0}{\mathrm{\Σ}}}{\mathrm{Workload}}_{M_i,t}}{3*{\mathrm{WorkBase}}_W}=5.81$

${\mathrm{\Γ}}_1^{\′}=\frac{W}{E_{t_1}}=\frac{5.81}{6}=0.968$

Deviate 1=| Γ ₂-Γ |=| 0.968-1|=0.031

Deviation ratio 1,=31 ‰

Other sampled points, same t ₁Computing formula, can add up obtaining following table:

The real work efficient of sampling

The sampling time point	??t 1	??t 2	??t 3	??t 4
					Real work efficient	??5.81	??5.80	??5.79	??5.78
??Γ′	??0.968	??0.967	??0.965	??0.963
					Deviate	??0.031	??0.033	??0.035	??0.037

The sampling time point	??t 1	??t 2	??t 3	??t 4
					Deviation ratio	??31‰	??33‰	??35‰	??37‰

Stability bandwidth is analyzed:

Actual stability bandwidth

In adopting point, stability bandwidth exceeds 5 ‰, and real work efficient is lower than schedule work efficient, so plug wire link work efficiency is low, but through internal staff's investigation, the employee work ability that find to participate in the plug wire link is strong, and actual average work efficiency also reached specialty and require level, is not that employee's reason causes, but stability bandwidth shows the real work inefficiency, therefore, illustrate that the formulation of schedule work efficient time is higher, should the plan for adjustment efficient time.Constant when real work efficient, schedule work efficient is adjusted into T=5.8, calculates the back again:

The sampling time point	??t 1	??t 2	??t 3	??t 4
					Real work efficient	??5.81	??5.80	??5.79	??5.78
??Γ′	??1.001	??1	??0.998	??0.997
					Deviate	??0.001	??0	??0.002	??0.003
Deviation ratio	??1‰	??0‰	??2‰	??3‰

Actual stability bandwidth=1.5 ‰

After the adjustment, as can be seen at the curve sampling number according to interior stability bandwidth value less than 5 ‰, so plug wire link working efficiency situation is good.

3, debugging link sampling statistics:

T=6.5 in the debugging link.

During debugging,, be parallel model, calculate according to model one for parallel production line work

At sampled point t ₁The time, $E_{t_1}=\frac{\underset{i=1}{\overset{3}{\mathrm{\Σ}}}\underset{t=t_1-\frac{1}{2}}{\overset{t_1+\frac{1}{2}}{\mathrm{\Σ}}}{\mathrm{Workload}}_{M_i,t}}{3*{\mathrm{WorkBase}}_1}=6.31$

${\mathrm{\Γ}}_1^{\′}=\frac{W}{E_{t_1}}=\frac{6.32}{6.5}=0.971$

Deviate 1=| Γ ' ₁-Γ |=| 0.971-1|=0.029

Deviation ratio 1,=29 ‰

Other sampled points, same t ₁Computing formula, can add up obtaining following table:

The sampling time point	??t 1	??t 2	??t 3	??t 4
					Real work efficient	??6.31	??6.38	??6.36	??6.35
??Γ′	??0.971	??0.982	??0.978	??0.976
					Deviate	??0.029	??0.018	??0.022	??0.024
Deviation ratio	??29‰	??18‰	??22‰	??24‰

Stability bandwidth is analyzed:

Actual stability bandwidth

In adopting point, stability bandwidth all exceeds 5 ‰, and real work efficient is lower than schedule work efficient, therefore plug wire link work efficiency is low, finds through the personal investigation, and the employee who participates in debugging is the new person of work company, operate also unskilled, real work efficient is for arriving professional requirement, and therefore according to deviation ratio, company has found the low true cause of debugging Link Efficiency.Company has carried out the technical ability intense session to the related personnel pointedly, has increased substantially debugging employee's work efficiency.Staff training post-sampling data are as follows:

The sampling time point	??t 1	??t 2	??t 3	??t 4
					Real work efficient	??6.51	??6.49	??6.52	??6.49
??Γ′	??1.002	??0.998	??1.003	??0.998
					Deviate	??0.002	??0.002	??0.003	??0.002
Deviation ratio	??2‰	??2‰	??3‰	??2‰

Stability bandwidth is analyzed:

Actual stability bandwidth

After the staff training, as can be seen at sampling number according to interior stability bandwidth less than 5 ‰, therefore it is good to debug the link working efficiency situation.

4, assembling link sampling statistics:

T=7.5 in the assembling link.

During assembling,, be parallel model, calculate according to model one for parallel production line work

At sampled point t ₁The time, $E_{t_1}=\frac{\underset{i=1}{\overset{3}{\mathrm{\Σ}}}\underset{t=t_1-\frac{1}{2}}{\overset{t_1+\frac{1}{2}}{\mathrm{\Σ}}}{\mathrm{Workload}}_{M_i,t}}{3*{\mathrm{WorkBase}}_1}=6.31$

${\mathrm{\Γ}}_1^{\′}=\frac{W}{E_{t_1}}=\frac{6.31}{6.5}=0.971$

Deviate 1=| Γ ' ₁-Γ |=| 0.971-1|=0.029

Deviation ratio 1,=29 ‰

Other sampled points, same t ₁Computing formula, can add up obtaining following table:

The sampling time point	??t 1	??t 2	??t 3	??t 4
					Real work efficient	??7.46	??7.49	??7.39	??7.56
??Γ′	??0.995	??0.999	??0.985	??1.008
					Deviate	??0.005	??0.001	??0.015	??0.008
Deviation ratio	??5‰	??1‰	??15‰	??8‰

Stability bandwidth is analyzed:

Actual stability bandwidth

Stability bandwidth has exceeded the scope of plan stability bandwidth.In adopting point, have only the deviation ratio of t3 sampled point to exceed the plan deviation scope.Through in-house investigation, finding has the staff to withdraw from account of illness midway one day in the t3 sampled point time period, therefore had influence on real work efficient, and real work efficient has returned to level at ordinary times after sick employee does over again, and judges thus, and assembling link working efficiency situation is good.

By this based on the production optimization system of dual-progress factor and the introducing of optimization method thereof, feedback data can reflect the problem of concrete link effectively, and judgement by deviation ratio, concrete link is investigated and adjusted, can improve the efficient of whole piece streamline with optimized means.

The production of people's machine production line improves the correspondence that need do:

1, the data of gathering is carried out computational analysis accurately, judge the optimization degree

2, source of error analysis: at first analyze inner reason, whether have special situation to take place, as staff redeployment, ask for leave etc.; Analyst's work efficiency compares personnel's work efficiency and average work efficiency again, makes judgement.External cause, the measurement that baseline is set need be set baseline by experienced staff, for irrational baseline setting, also needs the staff in time to adjust by the feedback of actual stability bandwidth.

Because the following feedback that continues monitoring has been carried out continuous optimization to streamline, make original uncontrollable streamline throughput rate at last, become controlled, clear and definite control, improved yield-power greatly.

Claims (6)

1. production optimization system based on dual-progress factor, it is characterized in that forming by data collection module, production efficiency curve map analysis module and data feedback control module, the collection of the raw data that is used for evaluation work efficient wherein, production efficiency tracing analysis module is made up of workload conversion, curve plotting and curve display three parts.

2. the production optimization system based on dual-progress factor according to claim 1 is characterized in that data collection module is made up of a set of counters.

3. the production optimization system based on dual-progress factor according to claim 1 is characterized in that native system is as the basis of realizing with people's machine production line production system.

4. the production optimization method based on dual-progress factor the steps include:

(1) data aggregation: finished by data collection module, data collection module is made up of a set of counters, and the unit interval of counter image data is Δ t, the unit interval of representative from the t1 time to the t2 time.Each stream line operation personnel is a role in counter module, and counter is whenever collecting the work that the role finishes in Δ t, and counter will add 1, all working amount that counter can be added up each role respectively and finished;

(2) production efficiency tracing analysis: comprise workload conversion, curve plotting, curve display three steps composition,

First step: workload converts: at first, set baseline value, establish: $\mathrm{\Γ}=\frac{W}{T}=1$

Wherein, W is the real work efficient time; T is the schedule work efficient time.

$T=\mathrm{n\Δt}$ Plan T in the time amount of finishing the work be X;

Second portion: tracing analysis:

Step1: with running time and the ratio of schedule work time is the longitudinal axis, promptly is the longitudinal axis with Γ; Time shaft is a transverse axis;

Step2: datum line be free in one of Γ=1 curve with transverse axis, the work efficiency time that obtains in the Δ t time is sampled point, will become the running time curve after the connection of neighbouring sample point;

Step3: the sampled point computing method are: ${\mathrm{\Γ}}^{\′}=\frac{E_{t_0}}{T},$ Calculating because the difference of production models is divided into dual mode;

Model one: when production models are concurrent execution,

Computing formula as follows:

$E_{t_0}=\frac{\underset{i=1}{\overset{N}{\mathrm{\Σ}}}\underset{t=t_0-\frac{W}{2}}{\overset{t_0+\frac{W}{2}}{\mathrm{\Σ}}}{\mathrm{Worklood}}_{M_i,t}}{N*{\mathrm{WorkBase}}_W}$

Get a fixing moving window size W during calculating;

Model two: when production models are that serial is carried out or combination is carried out constantly,

Computing formula as follows:

$E_{t_0}=\frac{\underset{i=1}{\overset{N}{\mathrm{\Σ}}}\underset{t_0}{\overset{0}{\mathrm{\Σ}}}{\mathrm{Worklood}}_{M_i,t}}{N*{\mathrm{WorkBase}}_W}$

Γ ' _iDeviate=| Γ ' _i-Γ |

(3) data FEEDBACK CONTROL:

Step1: calculation deviation value.Under the normal condition, calculate

Value should be near horizontal reference value 1.0,

Represent work efficiency stable good, otherwise the state representative is unusual.

5. a kind of production optimization method based on dual-progress factor according to claim 4 is characterized in that abnormal conditions are as follows in the step (3):

First kind: continuous coverage in a period of time, find It is bigger to fluctuate: this illustrates unstable working condition, can illustrate generally what problem has appearred in individual working condition, needs on-the-spot investigation reason; The measurement of stability bandwidth D:

If time range [t ₁, t ₂], then the fluctuation of the production efficiency in this segment limit D can weigh with following formula:

${D_{[t_1,t_2]}}^2=\frac{\underset{t=t_1}{\overset{t_2}{\mathrm{\Σ}}}{(E_t-1)}^2}{(t_2-t_1)/\mathrm{\Δt}}$

Second kind: continuous coverage in a period of time, find Departed from 1.0 (higher or on the low side) in general, then can illustrate: the low or organizer and governor of the too high situation two of individual productivity, individual productivity need adjust the WorkBase of a drag _WReference value.

6. according to claim 4 or 5 described a kind of production optimization methods, it is characterized in that above step realizes in interactive mode based on dual-progress factor.