THIS PROJECT TUBITAK Sanayiye Yönelik Lisans Bitirme is ... · Sanayiye Yönelik Lisans Bitirme...

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201894%

improvement

DAILY PLANNING DURATIONINDUSTRIAL ENGINEERING

PRODUCTS9LIN

ES

ADVISORSACADEMIC

First Stage

6TEAM MEMBERS

I N D U S T R I A LE N G I N E E R I N G

for i = 2 to lastrow then step 2

…Set kapasiteSheets(“AtananSipar …

SYSTEMDECISION SUPPORT

Schneider Electric

Nilay YAPICI

Deniz TÜRSEL ELİİYİSel ÖZCAN TATARİSinem ÖZKAN Ender UYMAZ

Elif ERCANAlper UYAR Fatih AKAMCA

Ece BAŞAR İrem AMAÇPınar YUNUSOĞLU

Has been established in 1836, in FranceSchneider Electric Izmir was first established in Kemalpasa-Izmir in 1997 and moved to Manisa Organized Industrial Zone in 2009.

14 different products are produced under the same roof that includes medium voltage trunks and types of equipment and low voltage panels.

14 different products are produced under the same roof that includes medium voltage trunks and types of equipment and low voltage panels.

(4)(5)(6)

∑ X = q

Y Y < M

X < MY

(2)Min L = ∑ Tard + ∑ (1- ) Earl =1 =1

N N

n, t

n

n, t T - {t }

nt

nt

t = 1

T

n

nt

nt

nt

nt n(t+1)

Y < (1- ) n(t+1)

(3)∑ X < Cap k , tkt

nt

last

(7)n, t T - {t }∈last

q ∑ X < M(1- )nt

ni

t

n (8)n, t T - {t }∈last

X = The number of products produced for order n on day t

1, if X > 0 0, otherwise

1, if order n is satisfied on day t 0, otherwise

Tard = Number of days delayed of the tardy order nEarl = Number of early days of early order n

Y =

= = Tardiness penalty coefficient per dayCap = The capacity of the production line k in day td = Due date of the order n

q = Quantity of the order nt = Last day of the planning horizon

M : Big number

P = Preemptive priority factor of lateness objectiveP = Preemptive priority factor of order spliting objective

First Priority Goal: Minimization of Total Lateness

Second Priority Goal: Minimization of Total Number of Orders Split

New constraint (19) is added to the model to guarantee the optimal value from the first stage.

L is the optimal value for the first-priority goal of the model in the first stage.

Type something

*

(15)X Z {0} n, t

(17)Y , {0,1} n, t

nt

ntTard > (∑ t ) d

t = 1

T

n n (10)n

25

ntEarl > d (∑ t )

t = 1

T

n n (11)n

∑ X < Cap (12)t, n N , k = 1nt

1

4

n N

kt ∈∈

1

23

∑ X < C (13)t, n N , k = 3nt

n N

kt ∈∈

4

5 63

∑ X < Cap (14)t, n N N , k = 3nt

n N N

kt ∈

ntnt∈

+∈

5 6⋃⋃

⋃(16)Tard , Earl Z {0} nn n

∈+⋃

2

MODELMATHEMATICALMATHEMATICAL

t ∈ T

{{

I = Set of product groupsT = Set of daysN = Set of customer ordersN = Set of customer orders for product group i N N K = Set of production linesL = Set of customer orders that are produced on line k L N

Parameters

Main Objective Function: Minimizes total lateness and total numbers of split with preemptive priority factors: and

PREEMPTIVE GOAL PROGRAMMING MODELP P1 2

Capacity limitation

} }

Calculates tardiness} Calculates earliness

Specific capacity constraints for RICB and LF/GMH CB production lines

} To control the production of each order

}

Domain of decision variables

Demand satisfaction

To control the order splitting

∑ = 1nt

(9)n

(18)Min ∑ ∑ Yn = 1

N

t = 1

T

nt

(19)∑ Tard + ∑ (1- )Earl < Ln = 1

N

n = 1

N*

n n

Second Stage

SENSITIVITY ANALYSIS

ADVISORCOMPANY

PLANNING PROJECTPRODUCTION AND CAPACITY

P R O B L E M D E F I N I T I O N

P R O B L E M D E F I N I T I O N

S Y M P T O M S

S Y M P T O M S

Home AutomationIntegrated Building and AutomationIndustrial Automation and ControlElectrical Distribution and Control

MACRO SYSTEM ANALYSISFields of

Activity

MICRO SYSTEM ANALYSIS

6 ProductionLines

7 ProductGroups

450Technical Staff 130

TUBITAK2209-B

Administrative Staff

94%DAILY PLANNING

DURATION

IMPROVEMENTS

PRODUCTIONAND

CAPACITYPLANNING

PROJECT

PRODUCTIONAND

CAPACITYPLANNING

PROJECT

PRODUCTIONAND

CAPACITYPLANNING

PROJECT

PRODUCTIONAND

CAPACITYPLANNING

PROJECT

Manual activities in the planing process

Early and Tardy Orders

B. Karimi, S.M.T. Fatemi Ghomi, J.M. Wilson. 2003. “The capacitated lot sizing problem: a review of models and algorithms”, Omega 31 (2003) 365 – 378.Gicquel, C., Minoux, M., Dallery, Y. 2008. “Capacitated Lot Sizing models: a literature review.”, Hal-00255830.Sawik, T. 2003. “Integer Programming Approach to Production Scheduling for Make-To-Order Manufacturing”, Mathematical and Computer Modelling 41 (2005) 99-118.Wang, Y. M., Parkan, C. (2007). “A preemptive goal programming method for aggregating OWA operator weights in group decision making”, Information Sciences 177 (2007) 1867-1877.

90Min/Day

*

C O M P U T A T I O N A L R E S U L T S

C O M P U T A T I O N A L R E S U L T S

Decreasing the total lateness of customer orders

Decreasing the duration of the production planning process by automatizing the current system.

H E U R I S T I C M E T H O DH E U R I S T I C M E T H O D

94%

SuccessCriteria

R E F E R E N C E SR E F E R E N C E S

Sets

Decision Variables

THIS PROJECT is funded by

Sanayiye Yönelik Lisans Bitirme Tezi Destekleme Programı

ON-TIMEDELIVERY

86%

Get data from related spreadsheets

Is order being produced on

relatedlines?

RI CB HATTI HAFTALIK ÜRETİM MİKTARI

PREMSET HATTI HAFTALIK ÜRETİM MİKTARI

LBS HATTI HAFTALIK ÜRETİM MİKTARI

LF & GMH CB HATTI HAFTALIK ÜRETİM MİKTARI

LF KUTUP HATTI HAFTALIK ÜRETİM MİKTARI

RI MCH HATTI HAFTALIK ÜRETİM MİKTARI

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