Specific management tools and her practical suitability for the beverage industry

Dipl.-Ing. Michael M. Braitinger, Business Management and Economics, Faculty of Business and Economics, Mendel University in Brno,

michael.braitinger@scb-consulting.de

Abstract

The beverage industry in Europe is characterized by mass production. To produce beverages

complex technical systems are necessary. These systems are capital intensive, both in

investment and in the production phase.

The refinancing of such investments must be seen against the background of a little

growing sales and the behavior of a polypolistic market for beverages.

These investments are more combinations of labor rationalizations together with

technological improvements, there are now less capacity expansions in consideration as it was

during the last decades. These investments alone are no guarantee for economic success.

Optimal use could be achieved only through the permanent application of management tools.

The goal of these tools is to avoid losses, increasing availability of production and the

improvement of the overall equipment effectiveness (OEE).

As a part of this study the possibilities of certain tools are also shown.

In an empirical long-term observation project (from 2008 – 2012), the Overall

Equipment Effectiveness (so called OEE) of two bottling plants in the beverage industry have

been studied. The studies took over 5 years and have been carried out based on the calculation

methodology for OEE as a management tool. In addition to this, the empirically collected data

were processed with the German “DIN 8782”, to highlight the suitability of this method for

this project. In this paper, the shape of the data analysis and the results thus obtained is

shown.

Key Words

Bottling line utilization, Overall equipment effectiveness, DIN 8782, long term production

monitoring.

Introduction

Production and sale of beverages in Germany take place in a polypolistic market. The

beverage industry is characterized by mass production. Until about 1990 drinks were bottled

in glass or metal containers, such as cans or kegs, or barrels of beer.

The introduction of PET bottles instead of glass bottles as packaging for soft drinks in Europe

has changed the beverage market sustainable. These changes affect both the logistics and

production engineering. In connection with the introduction of the PET bottle substantial

investment in bottling and packaging PET bottles are made. The investments in these PET

bottling lines were capital intensive.

With reference to the circumstances of a polypolistic market system, this development also

brought up significant disadvantages for low capitalized firms in polypolistic market events.

Such disadvantages were a lack of attractiveness of the product and its packaging, high

logistics costs compared to PET goods handling and the still remaining various risks from the

material Glass.

It was observed that due to the capital required for the acquisition of such filling, competitive

pressures within the producers increased.

Here arises a typical dilemma of the beverage industry:

On the one hand, the plants have to run as long as possible without interruption to achieve a

profitable asset utilization, on the other hand, the systems need to be flexible to respond

quickly to market demands, such as small batch or special packaging.

In addition, it should be noted that the beverage manufacturers have the choice between two

technologically different filling systems. Both systems have different investment financing

needs. This leads to different overheads in product pricing. This advantage or disadvantage

surfaced only after the end of the amortization period.

The author carried out a long-term empirical study of the Overall Equipment Effectiveness1

(OEE)2 for these technological different filling lines.

All results of this long-term monitoring are the subject of a thesis of the author.

The filling lines – as shown in Fig. 1 - have basically a similar technical layout. Both filling

and packaging plants produce Icetea in PET bottles, 6 bottles each with a capacity of 1.5 liters

as packaging unit.

The filling process itself was technologically different. The difference in the technology is the

type of the product preservation during bottling.

In the Cold aseptic filling line filling (CAF) the packaging (bottle), the product and the

closures are made germ-free through physical methods (pasteurizing effects).

In the cold sterile filling line filling (CSF) the product will be sanitized using a specific

chemically method3 through microbiological oxidation effects.

1 NAKAJIMA, S., Introduction to TPM, USA, Productivity Press Cambridge

Massachusetts, 1988, pp 27, ISBN 915299232 2 May, Constantin, Koch, Arno (2008), Overall Equipment Effectiveness (OEE) – Tool

to improve productivity (Werkzeug zur Produktivitätssteigerung), Journal of Consulting

(Zeitschrift für Unternehmensberatung) Vol 06/08, pp.245-250, Erich Schmidt Press,

Berlin, ISSN 1863-3889 3 The method relies on the use of Dimethyldicarbonate. It is marketed under the trade

name Velcorin ® from Lanxess AG. Dimethyldicarbonate is approved as a food

additive number E 242 and as free of declarable for 'cold sterilization' processes under §

(Source: own)

Figure 1 Bottling process mapping

Objectives and methodology

As part of a long-term empirical observation, it was necessary to find a methodological

approach to data collection and processing. The collection of primary data had to be done by

the operator.

After manual plausibility control, a simple algorithm to process the data should be available.

The objective of the data processing will be statements concerning the productivity and

utilization of the examined time filling equipment.

In the beverage industry, different Management tools are used for analyzing production

situation and economy. Some of these management tools are listed below:

5 (COMMISSION REGULATION (EC) No 2165/2005 of 20 December 2005

amending Regulation (EC) No 1493/1999 on the common organization of the wine.) of

the additive approval regulations for non-alcoholic flavored drinks, wine, non-alcoholic

wine and Liquids

Stretch blow

molding Machine

Stretch blow

molding Machine

Air conveying

system

Air conveying

system

Cold Aseptic

Filling bloc

with rinsing

filling and

closing.

Cold SterilizationFilling bloc

with rinsing

filling and

closing.

PET preformsPET preforms

Closures, product

and bottle

sterilization

unit

Beverage

mixer

Supply: water, ingredients, sugar, flavours etc.

Auxiliaries units: Electric and thermal power,compressed air supply, process gas media (CO2,

N2), process supporting chemicals, et alt.

Beverage

mixer

Human Resources

Labelling Labelling

Multipack

systems

Multipack

systems

Palletizer Palletizer

Stretch Wrapper Stretch Wrapper

Warehouse

Supply

Bottling

Distribution

Technical

additives

Table 1 : Management tools

Source: Evers, H., Berlin (11/2013), „Overall Equipment Effectiveness or the famous DIN

8782 - Comparison of key factors in the value chain” Presentation at the 13th Congress of the

International Fresenius "Sensitive Beverages

Table 2 : Management tools

Source: Evers, 2013

Research aerea Management tool

To high production costs OEE, OAE; GAE

to low plant productivity OEE = Overall Equipment Effectiveness

Too low operational productivity OAE = Overall Asset Efficiency

Lack of transparency of machine losses GAE = Gesamtanlageneffektivität

Lack of transparency in the capacity calculation

Frequent deviations from the plan (contract duration /

contract term

Excessive stocks Kanban

High inventory costs Kanban = Analysis Pull / Pull Principles

Long lead times

Excessive stocks QCO, SMED

to high capacity losses due to conversions QCO = Quick Change over

Increasing variety and lack of capacity SMED = Single Minute Exchange of Die

unclear situation Value Stream Map

Inadequate definitions in the KVP Process

to high production costs

Quotas of returning goods

lack of capacity

Lack of order and cleanliness 5 S / 5 A / Muda

High productive time for searching and waiting

Nervous tension of personnel due to chaos in the

production

Recurring error

to high error rate Poka Yoke

Increasing number of customer complaints System to identify and avoid technical

Low quality rate mistake - key-lock-principle

High quality costs

Rarely flawless runs of processes

Recurring error

Too little change dynamics KVP / Six Sigma

Insufficient implemented improvements Six Sigma in combination with DMAIC =

Little motivated employees Define - Measure - Analyze - Improve -

Interface problems (example: production-> Planning,

production-> Logistics) Control

No KVP / Kaizen culture available

For long-term observation study on the availability of the filling lines the OEE method was

used with the internationally accepted accounting framework4.

Source: DIN 8782, (May 1984) Definitions for bottling lines and single components

Figure 2: Method of calculating DIN 8782

4 NAKAJIMA, S., Introduction to TPM, USA, Productivity Press Cambridge Massachusetts, 1988, pp 27,

ISBN 915299232

Working time (Definition Nr. 3.7 and 3.4 at DIN 8782)

Operating time

(Working time - sheduled shutdown time)

(Definition Nr. 3.5 and 3.4 at DIN 8782)

Net operating time

(Operating time - time for external

caused stoppages) (Definition at 3.3

-> DIN 8782)

effective operating time

(Definition Nr. 3.1 ->

DIN 8782)

Minus sheduled downtime time:

Process support time and tool

change (i.e change of packaging)

or startup of the process

Minus external caused stoppage times:

Operator failure, no supply of process

materials incl. power breakdown

Minus internal caused stoppage times:

technical defects in the line causing stopps or reduced

line speed

DIN 8782 timeline for beverage filling

Parameters for bottling lines acc. DIN 8782

Nominal output line in Bph or similar = QnA = produced goods ÷ time unit

Effective Output in Bph or similar = Qeff A = produced goods ÷ net operating time

Average Output in Bph or similar = Q m A = produced goods ÷ working time

Line utilisation % = φ A = Average Output ÷ Nominal Output ( Qeff A ÷ QnA)

Source: May, Koch, 2008

Figure 3 : Method of calculating OEE

Both methods - OEE5 and DIN 8782 - refer to the relation of production volumina and

operating times.

Data collection by the operator of the filling lines was restricted to a minimum.

Per calendar week following data had to be entered in a record sheet:

Scheduled Downtime

Downtime caused by external factors

Downtime Caused by line internal factors

Net operating time

Filling amount in bottles

Filling amount in hectoliters

5 NAKAJIMA, S., Introduction to TPM, USA, Productivity Press Cambridge Massachusetts, 1988, pp 27,

ISBN 915299232

Gross available time (24 hours / 7 days) The measured asset was purchased, installed and is

available for 24 hours, 7 days, all year

effective operating time

Available Output

effective Output

Minus

performance

losses:

reduced Speed,

short stoppage

correct

units

OEE Overall Equipment Effectiveness

avai

lab

ilit

y Gross available production time

No production

sheduled

Minus planned or sheduled

shutdown losses: failure, start-

up, set-up / adjust, tool

change, external limitations

A

B

C

Dper

form

ance

effective Output

Minus

defective

units

Qu

alit

y

F

E

Efficiency loosses

OEE % = Availability % x Performance % x Quality %

= (B ÷ A) x ( D ÷ C) x (F ÷ E) in %

With this information it is possible to meet the requirements for the processing of the data

material gained through the long-term observation for both the OEE and for the DIN 8782 as

seen in Tab. 3 and 4.

Table 3: Data processing scheme for the DIN 8782

Source: own

Table 4: Data processing scheme for OEE

Source: own

Results

This study is part of a long-term empirical observation on plant availability and describes the

methodology for recording and analyzing of these collected long-term data.

Modus operandi Calculation scheme for DIN 8782 units

A Working time hours per week

./. B Sheduled down time hours per week

= C Operating time hours per week

. /. D External down times hours per week

= E Net operating time hours per week

./. F internal failure time hours per week

= G effective operating time hours per week

H Nominal Outout in Bph Bottles per hour

I Produceed correct Goods Bottles per week

J = I ./. E Q eff a effective output in Bph Bottles per hour

K = I ./. A QmA average output in Bph Bottles per hour

L = K ./. H φ A line utilization in %

Calculation for OEE

A gross available production time

./. Aux. (sheduled shutdown times)

./. EFT (external limitations)

B effective operating time hours

Nominal Output line bottles per hour

C available Output bottles

./. IFT (short stoppage etc.) hours

D effective Output in h hours

E effective output in bottles bottles

F correct produced goods bottles

G OEE in % = (B ÷ A) x (D ÷ C) x (F ÷ E)

With the described methodology of data collection, it was possible to process these data

through application of the OEE and DIN 8782 model.

Different interpretations of the numerical values found are possible. But at one point, both

methods yield the same conclusion, namely, "OEE" and "Line utilization".

The study has a high proportion of manual data collection. Over the long term data entry

errors or inaccuracies evaluation by the operator were observed.

In order to avoid such errors in the future, Voigt6 reported from the results of the undergoing

project for the application of the OEE structure into a model for automated reporting systems

through the bottle filling process. This project inside the Technical University of Munich

researches how the application of the OEE supports improvements of the line availability

through the analysis of the data from the OEE point of view. Focuses on this research project

are among others the improvement of maintenance, reduction of casual failure times through

continuous line monitoring, reduction of defective goods.

The results of long-term observation point to differences between the systems. Based on the

obtained results, the OEE approach proves to be suitable for long-term observations and can

be performed by its simple calculation of structures also by the workers at the plant. For the

Management are the obtained results been useful as productivity indicators.

Table 5: OEE longterm results by filling line CSF

Source: own

6 Voight, T, (2011), Improvements of efficiency for bottling and packaging lines (Effizienzsteigerung bei

Abfüll- und Verpackungsanlagen), Chair of food packaging Technical university Munich, published at

“Der Weihenstephaner”, Nr. 1 (2011), p 24, Hans Carl Press, ISSN 0171-5089.

Definition 2008 2009 2010 2011 2012

A gross available production time in h 4.845,29 5.623,44 5.835,59 2.520,04 4.949,00

B effective operating time in h 4.304,39 5.022,38 5.188,14 2.191,67 4.073,93

C Available Output in bottles 90.392.190 105.469.980 108.950.940 46.025.070 85.552.530

D effective Output 85.387.050 97.761.930 100.858.800 36.099.840 85.081.080

E effective Output 85.387.050 97.761.930 100.858.800 36.099.840 85.081.080

F correct goods 67.740.990 82.753.118 85.407.814 34.754.443 65.435.496

G Nominal Outout in Bph 21.000 21.000 21.000 21.000 21.000

H Availability in % 88,84% 89,31% 88,91% 86,97% 82,32%

I Performance in % 94,46% 92,69% 92,57% 78,44% 99,45%

J Quality in % 79,33% 84,65% 84,68% 96,27% 76,91%

K OEE p.a in % 66,58% 70,07% 69,69% 65,67% 62,96%

OEE Overview for CSF

Table 6: DIN 8782 longterm results by filling line CSF

Source: own

Table 7: OEE longterm results by filling line CAF

Source: own

Table 8: DIN 8782 results by filling line CAF

Source: own

Definition 2008 2009 2010 2011 2012

A Working time 4.845,29 5.623,44 5.835,59 2.520,04 4.949,00

B Sheduled down time 513,91 584,73 609,94 301,98 829,20

C Operating time 4.331,38 5.038,71 5.225,65 2.218,06 4.119,80

D External down times 26,99 16,33 37,51 26,39 45,87

E Common operating time 4.304,39 5.022,38 5.188,14 2.191,67 4.073,93

F internal failure time 238,34 367,05 385,34 472,63 1.168,61

G effective operating time 4.066,05 4.655,33 4.802,80 1.719,04 2.905,32

H Nominal Outout in Bph 21.000 21.000 21.000 21.000 21.000

I Produced correct goods 2010 67.740.990 82.753.118 85.407.814 34.754.443 65.435.496

J Q eff a effective output in Bph 15.738 16.477 16.462 15.858 16.062

K Q mA average output in Bph 13.981 14.716 14.636 13.791 13.222

L φ A line utilization p.a in % 66,58% 70,07% 69,69% 65,67% 62,96%

The DIN 8782 Overview for CSF

Defintion 2008 2009 2010 2011 2012

A gross available production time in h 6.096,16 5.848,85 5.091,09 5.279,68 5.240,92

B effective operating time in h 3.914,86 3.779,35 3.389,01 3.504,64 3.554,10

C Available Output in bottles 93.956.640 90.704.400 81.336.240 84.111.360 85.298.400

D effective Output 62.362.560 58.386.480 52.937.760 81.506.880 83.741.520

E effective Output 62.362.560 58.386.480 52.937.760 81.506.880 83.741.520

F correct goods 59.016.570 57.964.890 51.549.594 59.819.910 61.960.032

G Nominal Outout in Bph 24.000 24.000 24.000 24.000 24.000

H Availability in % 64,22% 64,62% 66,57% 66,38% 67,81%

I Performance in % 66,37% 64,37% 65,09% 96,90% 98,17%

J Quality in % 94,63% 99,28% 97,38% 73,39% 73,99%

K OEE p.a in % 40,34% 41,29% 42,19% 47,21% 49,26%

OEE Overview for CAF

Definition 2008 2009 2010 2011 2012

A Working time 6.096,16 5.848,85 5.091,09 5.279,68 5.240,92

B Sheduled down time 2.083,06 1.866,75 1.584,25 1.666,52 1.621,95

C Operating time 4.013,10 3.982,10 3.506,84 3.613,16 3.618,97

D External down times 98,24 202,75 117,83 108,52 64,87

E Common operating time 3.914,86 3.779,35 3.389,01 3.504,64 3.554,10

F internal failure time 1.316,42 1.346,58 1.183,27 970,70 972,39

G effective operating time 2.598,44 2.432,77 2.205,74 2.533,94 2.581,71

H Nominal Outout in Bph 24.000 24.000 24.000 24.000 24.000

I Produced correct goods 2010 59.016.570 57.964.890 51.549.594 59.819.910 61.960.032

J Q eff a effective output in Bph 15.075 15.337 15.211 17.069 17.433

K Q mA average output in Bph 9.681 9.910 10.125 11.330 11.822

L φ A line utilization p.a in % 40,34% 41,29% 42,19% 47,21% 49,26%

The DIN 8782 Overview for CAF

Table 9: Results Concentrate of the long-term observation

Source: own

Source: own

Figure 4 : Long-term course of OEE and DIN 8782

The results show that the investigated filling line CSF is distinctly higher in the availability

and performance, but is inferior in quality factor of the bottling line ACF. In the course of five

years observing a trend towards improvement in productivity of the line ACF can be seen. In

contrast, a reduction in productivity can be seen in CSF system.

OEE / DIN 8782 Considerations 2008 2009 2010 2011 2012 Ø

for CSF p.a in % 66,58% 70,07% 69,69% 65,67% 62,96% 66,89%

for CAF p.a in % 40,34% 41,29% 42,19% 47,21% 49,26% 43,79%

Availability 2008 2009 2010 2011 2012 Ø

CSF 88,84% 89,31% 88,91% 86,97% 82,32% 87,19%

CAF 64,22% 64,62% 66,57% 66,38% 67,81% 65,89%

Performance 2008 2009 2010 2011 2012 Ø

CSF 94,46% 92,69% 92,57% 78,44% 99,45% 90,94%

CAF 66,37% 64,37% 65,09% 96,90% 98,17% 75,22%

Quality 2008 2009 2010 2011 2012 Ø

CSF 79,33% 84,65% 84,68% 96,27% 76,91% 83,87%

CAF 94,63% 99,28% 97,38% 73,39% 73,99% 86,13%

0,00%

10,00%

20,00%

30,00%

40,00%

50,00%

60,00%

70,00%

80,00%

2008 2009 2010 2011 2012

Uti

liza

tio

n i

n %

Year

Overview OEE or DIN 8782-> 2008 - 20121

for CSF p.a in % for CAF p.a in %

Discussion

Management decisions are often characterized by time and market pressure. Long term

planning for distribution in the beverage industry sometimes suffers due the dynamic of this

market. The influences of the weather conditions as well as the possibility of quick responses

against competition are imponderables for the production planning as well as the reliability of

the technical equipment. Consequently the focus of the management will be the choice for

bottling lines which high efficiency and defined cost structures.

Once a decision made for one or the other filling line system it can´t be revised without

further notice. And it can lead to economic losses due to calculation deficits. In polypolistic

market often determines the trade, what price the company can get its products. To avoid the

risk of losses to more expensive productions, the effectiveness of the operation must be kept

permanently high. For this purpose, the OEE supply a significant contribution method in the

context of Total Productive Maintenance with its visualization of productivity. OEE results

should be considered a starting point for further analysis in the field of Total Plant

Productivity. While OEE results have three areas namely availability, performance and

quality in focus, the productivity of evaluation according to DIN 8782 is only one of many

representations results.

Conclusion

With the indicated long-term observation of performance, availability and quality of two

bottling lines, it is also possible to observe positive or negative trends and react accordingly

based on the results found. OEE results should be considered a starting point for further

analysis in the field of Total Plant Productivity. The OEE method is used in many industries,

but only sporadically in the beverage industry, since productivity was either held by the

occasional application of DIN 8782 or their own rating systems. Even better, if as is common

in the automotive industry, the data at different locations would be anonymous collected in a

central database. With the Access for decision-makers they could experience their intentions,

weight their investments and act differently so also in the sense of sustainable finance capital.

References

EVERS, H., 2013: Overall Equipment Effectiveness or the famous DIN 8782 - Comparison

of key factors in the value chain, Paper presentation at the 13th Congress of the International

Fresenius "Sensitive Beverages" at Berlin

MAY, C., KOCH, A., 2008: Overall Equipment Effectiveness (OEE) – Werkzeug zur

Produktivitätssteigerung, Zeitschrift für Unternehmensberatung Vol 06/08, pp.245-250, Erich

Schmidt Press, Berlin, ISSN 1863-3889

DIN 8782, 1984: Begriffe für Abfüllanlagen und einzelne Aggregate, Standardization

Comitee Mechanical Engineering at the German Institute for Standardisation, Beuth Verlag

GmbH, Berlin, ISSN 0722-2912

NAKAJIMA, S., 1988: Introduction to TPM, USA, Productivity Press Cambridge

Massachusetts, 1988, pp 27, ISBN 915299232

VOIGHT, T, 2011: Effizienzsteigerung bei Abfüll- und Verpackungsanlagen, Chair of food

packaging Technical University Munich, published at “Der Weihenstephaner”, Nr. 1 (2011),

p 24, Hans Carl Press, ISSN 0171-5089.