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.