Thesis (MScEng)--University of Stellenbosch, 2005. / ENGLISH ABSTRACT: This report presents the application of the six sigma quality concept in solving a true
business problem. Six sigma is a quality improvement and business strategy/tool
developed by Motorola in the mid 1980s. It aims at delivering products and services that
approach levels of near perfection. To achieve this objective a six sigma process must not
produce more than 3.4 defects per million opportunities, meaning the process should be
at least 99.9997% perfect [Berdebes, 2003]. Motorola's success with six sigma
popularised the concept and it has now been adopted by many of the world's top
compames e.g. General Electric, Allied Signal-Honeywell, etc. All the six sigma
companies report big financial returns as a result of increased quality levels due to the
reduction in the number of defects. 'General Electric reports annual benefits of over $2.5
billion across the organisation from six sigma' [Huag, 2003].
The six sigma concept follows a five step problem-solving methodology known as
DMAIC (Define, Measure, Analyse, Improve, Control) to improve existing processes.
Each of these steps makes use of a range of tools, which include quality, statistical,
engineering, and business tools.
This report first gives a theoretical presentation on quality and six sigma, attempting to
answer the question 'What is six sigma'. A step-by-step guide on how to go through the
DMAIC problem solving cycle is also presented.
The six sigma concept was demonstrated by application to the colour removal process of
a continuous processing plant manufacturing refined sugar. Colour removal is a very
important process in sugar refining since the purpose of a refinery is to remove colour
and other impurities from the raw sugar crystals. The colour removal process consists of
three unit operations; liming, carbonation and sulphitation. Liming involves the addition
of lime (calcium hydroxide) required for the formation of a calcium precipitate in the
next unit operations. Carbonation is carried out in two stages; primary and secondary
carbonation. Both stages involve the formation of a calcium carbonate precipitate, which traps colour bodies and other impurities. Sulphitation occurs in a single step and involve
the formation of a calcium sulphite precipitate which also traps impurities. The pH and
colour are the main variables that are being monitored throughout the colour removal
process. Colour removal process
Raw sugar
Melting Carbonation Crystalli
~ Liming ~ c::J Secondary f+ Sulphitation ..
Sugar
sation
Figure 1: Colour removal process
The pH control of the two colour removal unit operations; carbonation and sulphitation,
is very poor and as a result the colour removal achieved is below expectation. This
compromises the final refined sugar quality since colour not removed in the colour
removal processes ends up in the sugar. The first carbonation stage (primary) fails to
lower the pH to the required specification and the second carbonation stage (secondary)
is highly erratic, the pH fluctuating between too high and too low. The sulphitation
process adds more sulphur dioxide than required and hence the pH is lowered below the
lower specification limit.
The six sigma DMAIC cycle was implemented in order to solve the problem of poor pH
control. The Define phase defined the project and identified the process to be improved.
The Measure phase measured the current performance of the process by collecting past
laboratory data with the corresponding field instruments data. The data was used to draw
frequency distribution plots that displayed the actual variation of the process relative to
the natural variation of the process (specification width) and to calculate process
capability indices. The Analyse phase analysed the data so as to determine the key
sources of variation. The Improve phase used the findings of the analyse phase to propose solutions to improve the colour removal processes. The Control phase proposed a control
plan so as to monitor and sustain the improvement gained.
The key findings of the study are presented below:
• Failure of the first carbonation stage to lower the pH to the required level is due to
insufficient carbon dioxide gas supply.
• The second carbonation reaction occurs very fast hence poor control will result in
high variability.
• The amount of colour removed is dependent on the input raw melt colour.
• The histograms of the colour removal unit operations are off-centered and display a
process variation greater than the specification width and hence a large proportion of
the data falls outside the specification limits.
• The % CaO and CO2 gas addition were found to be the key variables that control the
processes centering on target. The % CaO having a stronger effect in the liming
process and CO2 gas addition on the carbonation process.
• The variation between the field instrument's pH and laboratory pH is the key variable
that control the processes spread (standard deviation of the processes).
• The processes Cpk values are less than C, (Cpk<Cp) meaning the processes can be
improved by controlling the key variables that control centering (% CaO, CO2 gas
addition).
The processes capability indices are low, Cp<l meamng the processes are not
statistically capable of meeting the required specifications at the current conditions.
•
Based on the findings of the study, the following deductions are made for the
improvement of the colour removal processes in better meeting the required
specifications.
• Increase the CO2 gas supply to at least 4900 m31hr, calculated based on the fact that at
least 140 rrr' gas is required per ton of solids in melt [Sugar Milling Research Institute
Course Notes, 2002]. • Control the key variables identified to be the key sources of variation; % CaO, CO2
gas addition and variation between the field instrument's pH and laboratory pH.
Reducing variation in the % CaO and increasing CO2 gas supply will improve the
processes ability to maintain centering at the target specification. Maintaining a
consistent correlation between the two pH readings; field instruments pH and
laboratory pH will reduce the processes standard deviation and hence the processes
spread. Reduction in the processes spread will minimize the total losses outside the
specification limits. This will allow better control of the pH by getting rid of high
fluctuations.
• Control of the input raw melt colour is essential since it has an impact on the degree
of decolourisation. The higher the input colour, the more work required in removing
the colour.
In improving the colour removal processes the starting point should be in ensunng
process stability. Only once this is achieved, the above adjustments may be made to
improve the processes capability. The processes capability will only improve to a certain
extent since from the capability studies it is evident that the processes are not capable of
meeting specifications.
To provide better control and to ensure continuous improvement of the processes the
following recommendations are made:
• Statistical process control charts
The colour removal processes are highly unstable, the use of control charts will help in
detecting any out of control conditions. Once an out of control condition has been
detected, necessary investigations may be made to determine the source of instability so
as to remove its influence. Being able to monitor the processes for out of control
situations will help in rectifying any problems before they affect the processes outputs. • Evaluation of capability indices- ISO 9000 internal audits
Consider incorporating the assessment of the capability indices as part of the ISO 9000
internal audits so as to measure process improvement. It is good practice to set a target
for Cp, the six sigma standard is Cp=2, this however does not mean the goal should be
Cp=2 since this depends on the robustness of the process against variation. For instance
the colour removal processes at the current operating conditions can never reach Cp=2.
This however is not a constraint since for the colour removal processes to better meet pH
specifications it is not critical that they achieve six sigma quality. A visible improvement
may be seen in aiming for Cp=I.
On studying the effects of CO2 gas addition the total data points outside specification
limits reduced from 84 % to 33 % and by reducing the variation between field
instruments pH and laboratory pH for the secondary pH the total data points out of
specification reduced from 55 % to 48 %. These results indicate that by improving C, to
be at least equal to one (Cp=l) the total data points outside specification can reduce
significantly, indicating a high ability of the processes to meet specifications. Thus even
if six sigma quality is not achieved, by focussing on process improvement using six
sigma tools visible benefits can be achieved. / AFRIKAANSE OPSOMMING: Hierdie tesis kyk na die toepassing van die ses sigma kwaliteitskonsep om 'n praktiese
probleem op te los. Ses sigma soos dit algemeen bekend staan is nie slegs 'n
kwaliteitverbeteringstegniek nie maar ook 'n strategiese besigheidsbenadering wat in die
middel 1980s deur Motorolla ontwikkel en bekend gestel is. Die doelstellings is om
produkte en dienste perfek af te lewer. Om die doelwit te kan bereik poog die tegniek om
die proses so te ontwerp dat daar nie meer as 3.4 defekte per miljoen mag wees nie - dit
wil se die proses is 99,9997% perfek [Berdebes, 2003]. As gevolg van die sukses wat
Motorolla met die konsep behaal het, het dit algemene bekendheid verwerf, en word dit
intussen deur baie van die wereld se voorste maatskappy gebruik, o.a. General Electric,
Allied Signal-Honeywell, ens. Al die maatskappye toon groot finansele voordele as
gevolg van die vermindering in defekte wat teweeg gebring is. So by. beloop die jaarlikse
voordele vir General Electric meer as $2.5 biljoen [Huag, 2003].
Die ses sigma konsep volg 'n vyf-stap probleem oplossings proses (in Engels bekend as
DMAIC: Define, Measure, Analyse, Improve, Control), naamlik definieer, meet,
analiseer, verbeter, en beheer om bestaande prosesse te verbeter. In elkeen van die stappe
is daar spesifieke gereedskap oftegnieke wat aangewend kan word, soos by. kwaliteits-,
statistiese--, ingenicurs-cn besigheids tegnieke.
Die verslag begin met 'n teoretiese oorsig oor kwaliteit en die ses sigma proses, waardeur
die vraag "wat is ses sigma" beantwoord word. Daama volg 'n gedetailleerde stap-virstap
beskrywing van die DMAIC probleem oplossingsiklus.
Die toepassing van die ses sigma konsep word dan gedoen aan die hand van 'n spesifieke
proses in die kontinue suiker prosesserings aanleg, naamlik die kleurverwyderingsproses.
Hierdie proses is baie belangrik omdat die doelstellings daarvan juis draai rondom die
verwydering van nie net kleur nie maar ook alle ander vreemde bestanddele van die rou
suiker kristalle. Die proses bestaan uit drie onafhanklike maar sekwensiele aktiwiteite
waardeur verseker word dat die regte gehalte suiker uiteindelik verkry word. Tydens die eerste twee stappe is veral die pH-beheer onder verdenking, sodat die kleur
verwydering nie die gewenste kwaliteit lewer nie. Dit bemvloed op sy beurt die gehalte
van die finale produk, omdat die ongewenste kleur uiteindelik deel is van die suiker. Die
pH inhoud is nie net nie laag genoeg nie, maar ook hoogs veranderlik - in beginsel dus
buite beheer.
Die DMAIC siklus is toegepas ten einde die pH beter te kan beheer. Tydens die
definisiefase is die projek beskryf en die proses wat verbeter moet word identifiseer. In
die meetfase IS die nodige data versamel om sodoende die inherente
prosesveranderlikheid te bepaal. Die belangrikste bronne of veranderlikes wat bydra tot
die prosesveranderlikheid is in die derde-- of analisefase bepaal. Hierdie bevindings is
gebruik tydens die verbeteringsfase om voorstelle ter verbetering van die proses te maak.
Die voorstelle is implementeer en in die laaste fase, naamlik die beheerfase, is 'n plan
opgestel ten einde te verseker dat die proses deurentyd gemonitor word sodat die
verbeterings volhoubaar bly.
'n Hele aantal veranderlikes wat elk bygedra het tot die prosesvariasie is identifiseer, en
word in detail in die verslag beskryf. Gebaseer op die analise en bevindings van die
ondersoek kon logiese aanbevelings gemaak word sodat die proses 'n groot verbetering in
kleurverwydering getoon het. Die belangrikste bevinding was dat die huidige proses nie
die vermoee het om 100% te voldoen aan die spesifikasies of vereistes nie. Die hoofdoel
van die voorstelle is dus om te begin om die prosesveranderlikheid te minimeer of ten
minste te stabiliseer - eers nadat die doel bereik is kan daar voortgegaan word om
verbeteringe te implementeer wat die prosesvermoee aanspreek.
Ten einde hierdie beheer te kan uitoefen en vanasie te verminder IS die volgende
voorstelle gemaak: Statistiese beheer kaarte
Die kleurverwyderingsproses is hoogs onstabiel. Met behulp van statistiese beheer kaarte
is daar 'n vroegtydige waarskuwing van moontlike buite beheer situasies. Die proses kan
dus ondersoek en aangepas word voordat die finale produkkwaliteit te swak word.
• Evaluering van proses vermoee - ISO 9000 interne oudit
Die assesering van die prosesvermoee behoort deel te word van die interne ISO oudit
proses, om sodoende prosesverbeteringe gereeld en amptelik te meet. Die standaard
gestel vir C, behoort gedurig aandag te kry - dit is nie goeie praktyk om bv. slegs 'n
doelwit van C, = 2 soos voorgestel in ses sigma te gebruik nie, maar om dit aan te pas na
gelang van die robuustheid van die proses wat bereik is.
Daar is beduidende voordele bereik deur die toepassing van die DMAIC siklus. So het
byvoorbeeld die persentasie datapunte buite spesifikasie verminder van 84% tot 33%,
bloot deur te kyk na die effek wat die toevoeging van C02 gas tydens die proses het. Dit
toon dus duidelik dat, alhoewel die proses huidiglik nie die vermoee het om te voldoen
aan die vereistes van ses sigma nie, dit wel die moeite werd is om die beginsels en
tegnieke toe te pas.
| Identifer | oai:union.ndltd.org:netd.ac.za/oai:union.ndltd.org:sun/oai:scholar.sun.ac.za:10019.1/50467 |
| Date | 12 1900 |
| Creators | Nxumalo, G. L |
| Contributors | Van Wijck, W., Von Leipzig, K. H., Stellenbosch University. Faculty of Engineering. Dept. of Industrial Engineering. |
| Publisher | Stellenbosch : Stellenbosch University |
| Source Sets | South African National ETD Portal |
| Language | en_ZA |
| Detected Language | English |
| Type | Thesis |
| Format | 115 p. : ill. |
| Rights | Stellenbosch University |
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