Drive-Thru Loading Concept for In Plant Milk Runs

fml – Lehrstuhl für Fördertechnik Materialfluss Logistik

Prof. Dr.-Ing. Dipl.-Wi.-Ing. W. A. Günthner

Technische Universität München

fml – Lehrstuhl für Fördertechnik Materialfluss Logistik · Prof. Dr.-Ing. Dipl.-Wi.-Ing. W. A. Günthner · Technische Universität München

Drive-Thru Loading Concept for

In–Plant Milk Runs

Marco Dewitz

Stefan Galka

MHCL 2012

Belgrad

2 fml – Lehrstuhl für Fördertechnik Materialfluss Logistik · Prof. Dr.-Ing. Dipl.-Wi.-Ing. W. A. Günthner · Technische Universität München

Drive-Thru Loading Concept for In–Plant Milk Runs

Motivation and Basics 1.

Drive-Thru Loading concept 2.

Benchmark of Automated Loading Concepts 3.

Summary and Outlook 4.




Drive-Thru concept 2.





Challenges of lean production supply systems

reduction of stock JIT materials supply number of variants

increases

Manageable only by high-frequency and synchronized material supply



High-frequency material supply by tugger trains

Q

S

S

S

Q

S

S

S

1:1 transport 1:n transport

Benefits of tugger trains in comparison to forklifts

• Reduction of transport distances and therefore traffic volume

• Stabilization of material provision process and thus constant replenishment lead times

• Reduction of providing errors, thru sequencing material

Definition: tugger train for small load carriers

• Manually operated industrial trucks, which transport

bins from one material sources to different destinations

on one tour.

• Often several tugger trains are operated simultaneously,

which use the same material source.

Q

S

Material source

Transport destination



Challenge by providing small load carriers

Process for providing

small load carriers

High numbers of destinations

Small material reach per bin

High-frequency supply process Different weights per bin

Partially high weights per bin (15 kg)

Manual handling of bins in the production

Tasks for the process design

Efficent

Ergonomic

High number of bins per tour (search effort)

Speed

Zero defects

Automation of loading process for the tugger trains on the material source

Automatically Sequencing of bins for reduction the search effort









Concept

D:/MHCL Belgrad/3_Vortrag/Routenzug_Anim_Logo.avi



Collection of

goods in

station

Release of

transfer depth

Arrival of

tugger train at

station

Positioning of

tugger train in

station

Manual

release and

load transfer

Start of tour

and delivery

(7) Laser mark for exact positioning

(2) Automatic release by PLC

(3) Break rollers for smooth SLC

transport

Doubled capacity for decoupling

(1) between collection process and

delivery process

(4) Clearance-free couplings

(5) Restraint guided trailers

(6) Centering devices

(8) Direct visual contact to discover

possible errors

(9) Unrestricted grab area due to

intended frames

(10) Anti-squeeze protection

Technical Description









Retrieval ASRS

Concept 1 Concept 2 Drive-Thru

Transport SLC to

loading station

Buffering SLC in

loading station

Sequencing SLC

Loading SLC

on TS

Transport TS to

buffer

Buffering TS

Loading TS onto

tugger train

Start tourE

xp

lan

ati

on

Process step

Buffer time

Conveyor technique

1

2

3

4

5

6

7

8

9

Tugger train driver

Transport shelveTS

Worker loading station

Available automated loading technologies

• ASRS-retrieval usually not restricted to SLC

sequence

• Determined order of delivery established in

ASRS prezone by conveyor technique or highly

dynamic buffer

Concept 1

• Trailers are separated and combined in station

• Employee feeds loading station with trailers

manually

Concept 2

• Transport shelves are taken of the trailers by fork

lifter

• Automated feeding of transport shelves by

conveyor technology

Description of Automated Loading Concepts



Stock falls below

reorder level

Technical lead time

Provide material for

milk run loading

Recognize

demand

Submit order to

material source

Milk run cycle time

Deliver material

Restocking material

at workplacePhysical lead time

Information lead time

Information

flow

Material flow

Technical lead time

• Time that is required by automated systems to

prepare all goods for a specific tour

• Number of buffering stages and handling steps

determines technical lead time

• The smaller the technical lead time, the longer

orders for a specific tour can be accepted

Lower reorder levels

Lower stock at workstations

Lower stocks in transit

Conclusions for the Replacement time

Time

Start tour

Start retrieval

ASRS

Reduction of

technical lead

time up to 50%

11

1

23

4

+

567

8

23

4

+

5

6

78

23

5Concept 1 Concept 2 Drive Thru









Summary

Challenges

• Increasing number of variants

• More flexible production

equipment

• Smaller containers

• Greater amount of buy-in-items

Aims

• High reactivity

• Cost- and space-effective

• Transparent processes

• Security of supply

Procurement Process

Tugger trains can solve major problems of conventional procurement processes and are

becoming an increasing trend, especially in automotive sector

Available loading concepts come with major disadvantages

Benefits of Drive-Thru concept:

• Dynamic procurement process

… due to fewer handling steps and technical lead time

• Economical procurement process

… due to smaller equipment investments and rewquired floor space

• Ergonomic procurement process

… since no additional physical stress is caused by loading tasks

• Lean procurement process

… due to fewer handling steps and buffering stages



June 2012

• Prototype of the system designed and tested at the Institute fml

October 2012

• Publication of empirical study with 15 automotive companies and

suppliers

• Showing further fields of action regarding milk-run systems

July 2013

• Initial operation at a plant of an automotive supplier

Outlook

D:/MHCL Belgrad/3_Vortrag/Video_Versuchshalle.MOD

fml – Lehrstuhl für Fördertechnik Materialfluss Logistik

Prof. Dr.-Ing. Dipl.-Wi.-Ing. W. A. Günthner

Technische Universität München

fml – Lehrstuhl für Fördertechnik Materialfluss Logistik · Prof. Dr.-Ing. Dipl.-Wi.-Ing. W. A. Günthner · Technische Universität München

Backup


Route 1

… Tour n

DIMENSIONING OF TACTED IN-PLANT MILK-RUN SYSTEMS

Disambiguation

Definition: route

• A route describes a predefined track from one /

several different sources to different destinations.

• The route comprises different destinations

(e.g. Flow racks)

Definition: tour

• A tour is a trip of the tugger train on a route

• The tour can have a defined start time

(tacted milk-runs),

start immediately after the previous tour or

start when the tugger trains has reached an

appropriate load capacity

(both untacted milk-runs)

route 1

tour 1 … tour n

Starts at 9am Starts at 2pm



Sequenced tugger loading reduces the search effort

typical small parts tugger

with free unloading sequence


DIMENSIONING OF TAKTED IN-PLANT MILK-RUN SYSTEMS

Disambiguation

Definition: replenishment lead time (RLT)

• The RLT is the maximum time which passes between signaling the material requirement and

provision of new materials

• The RLT depends on the process (Information process and physical process)

• The following factors influence the RLT:

• Type of signaling material requirements (Bin-Kanban, eKanban, …)

• Technical lead times (e.g. time for retrieval in an automatic storage)

• Time for the physical delivery and provision of materials

• At the moment of signaling material requirements, the stock on the usage point must cover the

material consumption during the whole RLT.

time

Signaling of

requirements

Provision of

materials

at the source

Transport through

the tugger train

Material provision

at the usage point

waiting

time

Information

process

physical

Material flow

requirements

recognition

waiting

time

replenishment lead times

lead time

waiting

time



Challenges during the planning process

Planning and dimensioning of milk-run systems

Deviations in

demand Layout Type of bins

Replenishment

lead times

Technology

(Capacity)

Process

(Handling

time)

Tact

Number of milk-run

trains and drivers

Required service

level

Lead times

Parameters

Output

• No standardized planning method or tools (individual Excel-tools)

• Dimensioning based on average demand or worst case

• Reserves in capacity and process times to buffer deviations in demand

Lead times



Why take deviations in demand into consideration?

Time

Transport

amount

under-

utilization

over-utilization special process necessary

Trade-off between under-utilization (waste) and over-utilization (bottleneck in provision

process)

Defective

goods

Production

schedule

Ordering

procedure /

workers

Available capacity

Mean utilization



Task

Decision

Plan process and

technology

Determine number of milk-

run trains (procurement)

Detailed planning (route)

Implementation

Tasks

• Calculate the number of milk-run trains to

achieve a requested service level

• Define the tact time

• Verify whether number of routes / takt

time is feasible

Ma

teri

al-

Qu

elle

BO 1 BO 2

BO n ...

BO 4

BO 3

3

3 3

3

3

4 4

4

4

44

Supermarkt

3

5

Pro

du

kti

on

4314 4314 4314 4314

4314 4314 4314 4314

4314 4314 4314 4314

4314 4314 4314 4314

4314 4314 4314 4314

4314 4314 4314 4314

4314 4314 4314 4314

4314 4314 4314 4314

4314 4314 4314 4314

21

6

Leergut-Senke



Input data for the calculations

Process times Technology Demands

Model





Model

tF1

tF3

tF = tF1 + tF2 + tF3 + tF4 Zeitanteil für Fahrt

tB Zeitanteil für Beladung

tE Zeitanteil für Entladung

tS Zeitanteil für Stopp

tH Zeitanteil für Handhabung

Bahnhof Produktion

tF4

tB

tE

Leergutsammelplatz

1 2

jj-1

1 2

i

tF2

tH tH tHtS ……

Bedarfsort

HaltepunktZeit

an

teil

e R

ou

ten

zu

gp

rozess

Leg

en

de

nu

mb

er

of

bin

s

nu

mb

er

of

sto

ps

dis

tan

ce

tF X

tB (X)

tE (X)

tS X

tH X

Dependency of process times





Model

Number of trailers per train Number of bins per trailer

Maximum capacity per milk-run train

http://www.mwbgmbh.de/aktuelles2.htm





Model

0,00

0,01

0,01

0,02

0,02

0,03

0,03

0 20 40 60 80 100

• Mean demand and standard deviation

• Assignment of materials and workstations (WS)

• Location of workstations (Layout)



Problem-solving approach

WS 1

Material 1 Material 2 Material 3 Material 4 Material 5 Material 6

0,00

0,00

0,00

0,01

0,01

0,01

0,01

0,01

0,02

0,02

0 50 100 150 200 250 300

Combine individual demands at a single workstation

WS 2

Combine individual demands at a single workstation

Combine demands at workstations to one route

Route 1

0

0,1

0,2

0,3

0,4

0,5

0,6

0,7

0,8

0,9

1

0 50 100 150 200 250 300 350 400

• Qualitative representation based on an empirical study

• Deviation of individual materials higher than deviations of amount

combined on one route.

0

5

10

15

20

25

30

8 9 10 11 120

5

10

15

20

25

30

8 9 10 11 120

5

10

15

20

25

30

8 9 10 11 120

5

10

15

20

25

30

8 9 10 11 120

5

10

15

20

25

30

8 9 10 11 120

5

10

15

20

25

30

8 9 10 11 12

0

10

20

30

40

50

60

8 9 10 11 12

0

10

20

30

40

50

60

8 9 10 11 12


0

0,1

0,2

0,3

0,4

0,5

0,6

0,7

0,8

0,9

1

0 20 40 60 80 100


Problem-solving approach

Question

• How many/which workstations can be combined to one route?

Input data

• Demands (amount of bins) per workstation

• Sequence of workstations (Location in layout)

• Requested service level (95%)

• Maximum transport volume (time and capacity) 60 small load carriers

WS 1 WS 2 WS 1 WS 2 WS 3 WS 1 WS 2 WS 3 WS 4 + + + + + +

0

0,1

0,2

0,3

0,4

0,5

0,6

0,7

0,8

0,9

1

0 20 40 60 80 100

0

0,1

0,2

0,3

0,4

0,5

0,6

0,7

0,8

0,9

1

0 20 40 60 80 100KLT/Tour KLT/Tour KLT/Tour

max. transport

volume per tour

(time and capacity)

max. transport

volume per tour

(time and capacity)

max. transport

volume per tour

(time and capacity)

• Service level of 95% achieved.

• Utilization 35/60 = 58%

• Service level of 95% achieved.

• Utilization 40/60 = 67%

• Service level of 95% not achieved.

Variant 1 Variant 2 Variant 3

best feasible solution


Halle B6 mit AKL HRL (B7) Halle B8 Warenaus-gangslager

HRLals automatisierte

Puffer- und Sequenzierfunktion

AKLals automatisierte Vereinzelungs- und Sequenzierfunktion

Produktion

LKW

-En

tlad

eber

eich

LKW

-Ver

lad

eber

eich

StaplerloseVersorgung durch getaktete Routenverkehre

WA-Lager

Kaufteile - GLT

Kaufteile - KLT

Fertigware

Kundenleergut

StaplerloseEntsorgung durch getaktete Routenverkehre

Lieferantenleergut GLT/KLT


Task

• Planning of a new logistics concept

• Planning and dimensioning of structure

• Planning of milk-run processes

• Determine the number of routes and milk-run TACT time

• Definition of routes

Case study

Focus of case study



Material flow data

• 460 small load carriers/h (SLC)

• 34 large carriers/h

Challenge

• High demand deviations

Case study

Material

source



Case study

Route 1

Route 2 Route 3 Route 4

Route

5

Route 5

Route 6

Route 7

• 7 SLC-routes, tact time 45 min

• Capacity 50 SLC/Tour

• Requested service level of 95%

• Mean utilitzation of 80%



• Increasing use of milk-run concepts

• Dimensioning based on experience

• Deviations only taken into account as a safety addition

• Solution approach explicitly considers deviations

• Higher planning reliability

• 2 research projects at our

institute concerning

milk-run systems

Summary and outlook

Drive-Thru-Loading concept

Drive-Thru Loading Concept for In Plant Milk Runs

Documents