getview vol2 no9 september 2012

Committee of the Global Engineers & Technologists Review

Chief Editor Ahmad Mujahid Ahmad Zaidi, MALAYSIA

Managing Editor

Mohd Zulkifli Ibrahim, MALAYSIA

Editorial Board

Dr. Arsen Adamyan Yerevan State University

ARMENIA

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AZERBAIJAN

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CANADA

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JORDAN

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JORDAN

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JORDAN

Assoc. Prof. Dr. John Ndichu Nder Jomo Kenyatta University of Agriculture and Technology-

(JKUAT) KENYA

Prof. Dr. Megat Mohamad Hamdan Megat Ahmad The National Defence University of Malaysia

MALAYSIA

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MOROCCO

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PAKISTAN

Prof. Dr. Naji Qatanani An-Najah National University

PALESTINE

Prof. Dr. Anita Grozdanov University Ss Cyril and Methodius

REPUBLIC OF MACEDONIA

Prof. Dr. Vladimir A. Katić University of Novi Sad

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Prof. Dr. Aleksandar M. Jovović Belgrade University

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SRI LANKA

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TAIWAN

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Assoc. Prof. Chotchai Charoenngam Asian Institute of Technology

THAILAND

Prof. Dr. Hüseyin Çimenoğlu Instanbul Technical University (İTÜ)

TURKEY

Assistant Prof. Dr. Zeynep Eren Ataturk University

TURKEY

Dr. Mahmoud Chizari The University of Manchester

UNITED KINGDOM

Prof. Dr. David Hui University of New Orleans

USA

Prof. Dr. Pham Hung Viet Hanoi University of Science

VIETNAM

Prof. Dr. Raphael Muzondiwa Jingura Chinhoyi University of Technology

ZIMBABWE

Dear the Seeker of Truth and Knowledge

Journal writing. It is rather like keeping a diary; some consider, but it is actually we have to take far more seriously. Therefore, you might prefer to present your unpublished work as a poster or a talk, as a easier way rather than writing it through scientific manuscripts forms. However, the 5 times nominated Nobel Prize, Fritz Schaefer, who have published 1300 scientific publications said, “if it isn’t published, it doesn’t exist.”. This is means, that only through a publication, they will elevate it to the status of a legitimate; completed project worthy of discussion. By the increasing competition for the publication of scientific research that has led to an increased emphasis on determining the perceived "quality" or "status" of a specific journal, then scientists, like everyone else, want to publish papers in journals, especially in where their work is likely to have the highest impact. On this, over the past two decades there has been a marked shift in the way scientific journals are published and disseminated; shifted the reliance from the print versions of most journals; everything is now available on-line. Many journals are available from more than one source, and sometimes one source is free while the other is restricted-access and very expensive. All of this would be a matter of the interest, were it not for the now pervasive and inappropriate practice to the quality of an individual's research. Considering on this, journals like GETview are also certainly only want to publish original research that will have a significant impact and therefore it necessary to explain how your paper differs from previous work, why your paper is important, and what new insights it presents. This journal has been nearly two years in the making. It was a natural outgrowth of the expansion and it was decided that the journal should be published as an open-access online journal. It was also decided that we would endeavour to publish twelve issues a year. Since the GETview is also an online initiative designed to provide a platform for the disciplines of the engineering and technology sciences where students and professionals alike can engage in provoking and engaging explorations of knowledge that push the boundaries of disciplinary lines, by opening space for cross-disciplinary discussions, this journal hopefully can inspires an intersectional investigation and consideration of the issues that scholars in the early part of the 21st century recognize as most compelling in our changing world. This is due to throughout engineering and technology science have had profound impacts, positive and negative, on humankind, other species and the environment. Hence, in an ongoing effort to acquaint our readers with the prominent scholars making up the editorial board that advises and serves the Getview, we are honoured to provide the independent's evidence-based and authoritative information also the advice concerning engineering, technology, and science to policy makers, professionals, leaders in every sector of society, and the public at large. Certainly, involving yours; with the interest and expertise, through paper submitted and published in the Getview. Prof. Ahmad Mujahid Ahmad Zaidi, PhD. Chief Editor The Global Engineers and Technologists Review

©PUBLISHED 2012

Global Engineers and Technologists Review

GETview

ISSN: 2231-9700 (ONLINE)

Volume 2 Number 9

September 2012

All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted, electronic, mechanical photocopying, recording or otherwise,

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Printed and Published in Malaysia

Vol.2, No.9, 2012 1. SCREENING OF FIVE MEDICINAL PLANTS FOR TREATMENT OF TYPHOID

FEVER AND GASTROENTERITIS IN CENTRAL NIGERIA DAWANG, N.D. and DATUP, A.

6. TAGUCHI’S QUALITY IMPROVEMENT ANALYSIS OF THE SME BREAD MANUFACTURING HAERYIP SIHOMBING, HAFIZ, M.K., YUHAZRI, M.Y. and KANNAN, R.

© 2012 GETview Limited. All right reserved

CONTENTS

ISSN 2231-9700 (online)

GLOBAL ENGINEERS & TECHNOLOGISTS REVIEW www.getview.org

G.L.O.B.A.L E.N.G.I.N.E.E.R.S. .& .-.T.E.C.H.N.O.L.O.G.I.S.T.S R.E.V.I.E.W 1

DAWANG1, N.D. and DATUP2, A.

1, 2 Department of Science Laboratory Technology Plateau State Polytechnic

Barkin Ladi, PMB 02023, Bukuru, Plateau State, NIGERIA [email protected]

1.0 INTRODUCTION There has been gradual shift of recent, from the use of synthetic drugs in treatment of some diseases to plant products due to emergence of multi drug resistant phenomena. Higher plants are sources of drugs, which have made important contribution in the health sector in urban as well as rural communities especially in tropics and sub-tropics (Sofowora, 1993). It has been proven scientifically that some plants have many compounds that exhibit prominent effects on the animal system while some possess important therapeutic properties, which can be utilized in the treatment and cure of human and other animal diseases (Ogundare, 2007). Medicinal plants are cheap starting materials for the synthesis of new drugs and the chances of the body accepting preparations from plants are more than from a substance synthesized from laboratory (Sofowora, 1988). Also, Fansworth (2001) has reported that aqueous decoctions of drug have a greater bioavailability to the body than synthetic formulation today in the market. This is due to the fact that presentation of the active constituent of the plant material in the solubilized form brings about increase absorption of the extract by the body. It has been documented that the plant kingdom is a wider natural and better medicinal agents than what is provided by the chemist (Sofowora, 2003). Gatstron (1993) estimated that about 14 % of known antibiotics are produced by plants. It has been reported also that 95 % of traditional drugs in Africa come from plants. A World Health Organisation (WHO) survey in 1983 has also showed that developing countries are more interested than ever in making use of traditional indigeneous resources in implementing the primary health care (Ntiejumokwu, 1990). In recent years, the interest to evaluate plants possessing antibacterial activity for various diseases is growing (Clark and Hufford, 1993). Herbal medicine is still the main stream of about 75 to 80 % of the whole population, and the major part of traditional therapy involves the use of plant extract and their active constituents (Acaraya, 2008). Plants have also been reported to exercise antimicrobial activities against various pathogens (Oladunmoye, 2006). Erythrina senegalensis is known locally as ‘nte’, is an evergreen tree. The plant is used in traditional medicine to cure malaria, jaundice infections, gastro intestinal disorder, gastric ulcer, diarrhea, abdominal pain, headache and body weakness (Diallo, 2000). Khaya senegalesis has the bitter-tasting bark that is highly valued in traditional medicine. The bark decoctions are locally taken against fever caused by malaria, and against stomach complaints, diarrhea, dysentery and anaemia.

ABSTRACT

Aqueous extracts of Vitex doniana, Khaya senegalensis, Vernonia amygdalina, Psidium guajava and Erythrina senegalensis were screened for their potential antimicrobial activities against Salmonella typhi and Escherichia coli. The extracts were obtained by using water as solvent and the dilution of the various extracts were prepared and tested against the test organisms. The minimum inhibitory concentration (MIC) was detected for each plant extract. Phytochemical screening of all the extracts was carried out and showed the presence of Alkaloids, Saponins, Tannins, Flavonoids, Anthraquinones, Cardiac glycosides, Terpense and steroids, Anthraquinones, Cardiac glycosides, Terpense and steroids and Glycosides. The highest zone of inhibition was indicated by V. doniana of 11.5 mm followed by P. guajava of 11.4 mm on E.coli and S. typhi respectively while the P. guajava did not show any reasonable inhibition on E.coli. V. doniana has the lowest MIC of 50.0 mg on S. typhi and 100.0 mg on E.coli, P. guajava has 100.0 mg on S.typhi and 200.0 mg on E.coli , K. senegalensis has 200.0 mg on the test organisms, Vernonia amygdalina has 200.0 mg on and non on E.coli and Erythrina senegalensis has MIC of 200.0 mg on the organisms. These results indicate that V. doniana and P. guajuva are of better option or have better active ingredients for the treatment of infections caused by these pathogens. Keywords: Plant Extracts, Sensitivity, Escherichia Coli, Salmonella Typhi.

SCREENING OF FIVE MEDICINAL PLANTS FOR TREATMENT OF TYPHOID FEVER AND GASTROENTERITIS IN CENTRAL NIGERIA

Global Engineers & Technologists Review, Vol.2 No.9 (2012)

© 2012 GETview Limited. All rights reserved

2

Psidium guajavaq (guava) is a typical Myrtoideae with tough dark leaves that are opposite, simple, elliptic to ovate and 5 to 15 cm long. The term ‘guava’ appears to be derived from Arawak via the Spanish guayaba. The extracts from the leaves or bark are said to have therapeutic agents against cancer, bacterial infections, inflammation and pain. Vernonia amygdalina (Shuwaka) is commonly called bitter leaf. Leaf decoctions are used traditionally to treat fever, malaria, diarrhea, dysentery, hepatitis and cough as a laxative and as a fertility inducer. The dried flowers are used against stomach disorders. Vitex doniana is called “deap” by Pan speaking tribe in Plateau state, Nigeria. The plant is a widespread deciduous forest tree in the savannah. It is a small to medium sized tree up to 25 m tall, bole branches for up to 11 m and up to 90 to 160 cm in diameter. In traditional medicine, leaf sap is used as an eye drop to treat conjunctivitis and other eye complaints. The bark extract is used to treat stomach complaints and kidney troubles (Agunu et al., 2005). Locally dried and fresh fruits are eaten against diarrhea and as a remedy against lack of vitamin A and B. The fresh leaves are also used as vegetables and for soup. This study is designed to find out the antibacterial potentials of the plants against gastro intestinal diseases caused specifically by E.coli and Salmonella sp and to substantiate their acclaimed uses in the traditional medicine. 2.0 MATERIALS AND METHODS The leaves of Vernnia amygdalina and Psidium guajava and stem bark of Khaya senegalensis, Vitex doniana, Erythrina senegalensis were collected from Panyam and Kerang villages of Mangu local area of Plateau State. The desired plant parts were removed and thoroughly washed with distilled water. They were all air dried at room temperature. The dried plant parts were then grinded into fine powder using mortar and pestle.

2.1 Extraction of Plant Materials The aqueous extraction method was used according to Osaghae and Omeregbe (1977). 50 grams of each of the plant part was weighed and dissolved in 500 ml of distilled water and kept at room temperature for 24 hours for complete saturation. They were filtered through a filter paper (Watman No.1). The filtrates were evaporated to dryness using thermostatically controlled water bath regulated to 80 °C and then stored in sterilized sample bottles. 2.2 Phytochemical Screening

2.2.1 Test for alkaloids 2.0 ml of the extract in a test-tube, 5.0 ml of distilled water was added and shaken vigorously for 2 minutes, after which few drops of oil was added and observed for formation of an emulsion for presence of alkaloids.

2.2.2 Test for tannins 4.0 ml of distilled water in a test tube, 1.0 ml of extract was added and a few drops of 10 % ferric chloride solution was added and observed for blue-black or green to greenish black colouration for tannins.

2.2.3 Test for flavonoids 8.0 ml of distilled water was added to 2.0 ml of the extract, followed by few drops of ferric chloride solution and then observed for blue or green colour indicating the presence of flavonoids.

2.2.4 Test for anthraquinines 0.5 gram of the extract was added to 50 ml of chloroform and shaken for 5 minutes. The solution was filtered and the filtrate was shaken with equal volume of ammonia solution and then observed for a pink violet or red colour in the ammonical layer.

2.2.5 Test for cardiac glycosides 0.5 ml of extract was shaken in 2.0 ml of chloroform with the addition of few drops of conc. sulphuric acid and observed for reddish brown ring.

2.2.6 Test for terpenes and steroids (liebermann-burchard test) 2.0 ml of extract in a test tube, 1.0 ml of acetic anhydride was added and some few drops of conc. sulphuric acid was added carefully down the side of the test tube and observed for reddish brown color at the interphase.



3

2.2.7 Test for glycosides Small portion of extract was placed in 2 separate test tubes. 5.0 ml of sulphuric acid was added to extract in test tube A, distilled water to extract in test tube B as control. They were both heated for 45 minutes, allowed to cool then few drops of 0.2 m of NaOH was added and heated again with Fehling’s solution for 3 minutes and was observed for formation of a reddish brown precipitate in test tube A for the presence of glycoside.

2.3 Preparation of Antimicrobial Disc Whatman’s filter paper No. 1 was perforated using paper perforator and dispensed into screwed cap bottle. They were sterilized in an oven at 16 °C for 2 hours. Several dilution of the extract was made at 25 mg, 50 mg 100 mg and 200 mg respectively and the sterilized discs were saturated with the various concentration of the extracts aseptically. 2.4 Sensitivity Test A colony of the test organism was picked aseptically and inoculated into 10 ml of sterilized peptone water and 0.1 ml of the inoculums was transferred into the molten nutrient agar and poured into plates and swirled for a homogenous distribution and allowed to solidify. The discs saturated with the various concentrations of the plant extracts were aseptically picked and placed on the plates and allowed to stand for 30 minutes and then incubated at 37 °C for 24 hours. Zones of inhibition were measured in millimeter. 2.5 Minimum Inhibitory Concentration (MIC) The nutrient broth was prepared according to manufacturer’s instructions and was distributed into test tubes and a serial dilution of the extract was made for the six tubes with the seven test tube which was used as a control and 0.7 ml of the inoculums from the peptone water was aseptically transferred into all the seven test tubes and was covered and incubated at 37 °C for 24 hours and observed for turbidity. The least concentration of the extract that inhibited the growth of the test organisms was taken as the MIC.

The test Organisms is the clinical isolates of Escherichia coli and Salmonella sp were obtained from Church of Christ in Nations (COCIN) Hospital Panyam and General Hospital Barkin Ladi respectively of Plateau State, Nigeria.

3.0 RESULTS AND DISCUSSION All the plants extracts showed the presence of alkaloids, glycosides and anthraquinone. Tannins and flavonoids, tannins, cardiac glycosides were absent in Khaya senegalensis, Vernonia amygadalina and Psidium guajava respectively. Terpense and steroids were absent in all the plants except K. senegalensis and P. guavaja as shown in Table 1.

Table 1: Phytochemical screening

Metabolites/plants Vitex doniana

Khaya senegalenses

Vernonia amygdalina

Erythrina senegalenses

Psidium guajava

Alkaloids + + + + + Saponins + + + + + Tannins + - - + + Flavonoides + - + + + Glycosides + + + + + Anthraquinone + + + + + Cardiac glycosides + + + + - Terpense and Steroids - + - - +

Note: + is present, and – is absent. All the plant extracts exhibited antibacterial activity against Salmonella typhi and Escherichin coli. The zone of inhibilion ranges from 7.1 mm to 11.4 mm at the concentration of 50.0 mg to 200.0 mg for S. typhi (Table 2), however, for E.coli, the zone of inhibition ranges from 7.5 mm to 11.5 mm (Table 3).

Table 2: Sensitivity test on salmonella typhi

Concentration 25.0 mg 50.0 mg 100.0 mg 200.0 mg Vitex doniana NI 7.1 mm 9.0 mm 11.4 mm Khaya senegalenses NI 8.5 mm 10.0 mm 11.0 mm Psidium guajava NI 9.0 mm 11.0 mm 11.4 mm Vernonia amygdalina NI 8.0 mm 10.2 mm 10.6 mm Erythrina senegalenses NI 7.5 mm 9.5 mm 11.0 mm

Note: NI is no zone of inhibition.



4

Table 3: Sensitivity test on escherichia coli

Concentration 25.0 mg 50.0 mg 100.0 mg 200.0 mg Vitex doniana NI 9.5 mm 9.7 mm 11.5 mm Khaya senegalenses NI NI 10.5 mm 11.4 mm Psidium guajava NI NI NI 9.2 mm Vernonia amygdalina NI 8.0 mm 10.2 mm 10.6 mm Erythrina senegalenses NI 7.5 mm 9.5 mm 11.0 mm


The minimum inhibitory concentration of the plant extracts ranges from 50.0 mg to 200.0 mg against both S.typhi and E.coli. However, V. amygdalina showed MIC on E.coli only at 200.0 mg as shown in Table 4.

Table 4: Minimum inhibitory concentration (MIC) of the plants

Plants/ Test organisms Salmonella typhi Escherichia coli Vitex doniana 50 mg 100.0 mg Khaya senegalenses 100 mg 200 mg Psidium guajava 200 mg 200 mg Vernonia amygdalina 200 mg NI Erythrina senegalenses 200 mg 200.0 mg


This study indicates antibacterial activities of Vitex doniana, Khaya senegalensis, guajava, Vernonia amygdalina and Erythrina senegalensis on Escherichia coli Psidium and Salmonella typhi. This is in conformity with the work of Kilani (2006) who reported that these extracts if properly enhanced and harnessed could be very useful in health care delivery system for treatment of diseases. It was noticed that all the five plants used have antimicrobial activities on the test organisms (E.coli and Salmonela typhi) with V.doniana showing the highest antimicrobial activity on both pathogens with zone of inhibition of 11.4 and 11.5 mm on the S. typhi and E.coli respectively and with a minimum inhibitory concentration of 50.0 mg against S.typhi and 100.0 mg against E.coli. This could probably have been due to the fact that the deposits of the active ingredients or constituents in the plant materials is higher compared to the other plants used in this research (Kunle and Egharevba, 2009). This also augments the report of Agunu et al., 2005) who documented on the plant V. doniana to be effective in treatment of diarrhea. Flavonoids and tannins have also been found to constitute the antibacterial activities in medicinal plants in India (Ahmed and Beg, 2001). The presence of flavonoids in the plants must have exhibited direct antibacterial activity and suppression of bacterial virulence resulting to the antimicrobial activity seen in this study (Cushniea and Lambb, 2001). The next effective plant was P. guavaja (MIC of 100.0 mg). The use of guava in diarrhea, dysentery and gastroenteristis can also be related to guava’s documented antibacterial properties (Tona et al., 2000). For instance Kamath et al., (2008) reported the leaves of guava to be rich in flavonoids particularly quercetin which demonstrated antibacterial and anti diarrheal effects and was able to relax the intestinal smooth muscle and inhibited bowel contractions. The lectin chemicals in guava have been shown to bind E.coli (a common diarrhea – causing organism) preventing its adhesion to the intestinal wall and thus preventing diarrhea (Geidam, 2007) which goes to confirm its activity against E.coli as demonstrated in this study. The result of this investigation emphasizes the usefulness of the five medicinal plants in traditional medicine in treatment of dysentery, diarrhea, typhoid and various intestinal disorders and the need to enhance their usage in this regards. This is particularly of urgent interest considering the rate of multi-drug resistance strains of organisms including Salmonella sp. and E.coli currently emerging worldwide (Prescott, 2005). Moreover, most of these plants used are non-toxic as they have been commonly used in soup making and as vegetables by humans without complaint. 4.0 CONCLUSION The findings from this research indicate that Vitex doniana and Psidium guajava leaf extracts are effective in treatment of diseases caused by both Salmonella sp and Escherichia Coli. Thus, research on other plants extracts should be encouraged. REFERENCES [1] Agunu, A., Yusuf, S., Andrew, G.O., Zezi, A.U. and Abdulrrahman, E.M. (2005): Evaluation of Five Medicinal

Plants Used in Diarrhea Treatment in Nigeria. J Ethno pharmacol, Vol.101, Iss.1-3, pp.27-30. [2] Acharya, C.A., Deepak, K. and Shrivastava, A. (2008): Indigenous Herbal Medicine: Tribal Formulations and

Traditional Herbal Practices, Aavishkar Publishers Distributor, Jaipur – India. p.440.



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[3] Ahmed, I. and Beg, A.Z. (2001): Antimicrobial and phytochemical studies on 45 Indian Medicinal Plants against Multi-Drug Resistant Human Pathogens. J Ethno pharmacol, Vol.74, Iss.2, pp.113-123.

[4] Clark, A.M. and Hufford, C.D. (1993): Discco and Development of Novel Prototype Antibiotic for Opportunistic Infections Related to the Acquired Immunodeficiency Syndrome. In human medical agents from plants American chemical society (ACS Symposium Series 534), Washington, D.C., pp.228-241.

[5] Cushniea, I.P.I. and Lambb, A.J. (2011): Recent Advances in Understanding The Antibacterial Properties of Flavoniods. International of Antimicrobial Agents, International society of Chemotherapy (ISC) for infection and cancer. Vol.38, Iss.2, p.99.

[6] Diallo, D. and Paulsen, B.S. (2000): Pharmaceutical Research and Traditional Practitioners In Mali: Experiences With Benefit Sharing. In responding to bioprospecting (from biodiversity in the South to medicines in the North). Edited by: Svarstad H, Dhillion S.S. Spartacus Forlagi,pp.133-144.

[7] Farnsworth, N.R. (2001): The Present and Future of Pharmacognosy. News letter of the Americans society for pharmacognosy, pp.4-12.

[8] Galstron, A. (1993): Modern Medicine and Its Impact In Africa. In African medicinal plants university of Ife Press, Ile-Ife, pp.41-43.

[9] Geidam, Y.A., Usman, H., Abubakar, M.B. and Ibrahim, B. (2007): Effects of Aqueous Leaf Extracts Of Psidium Gujava on Bacteria Isolated From The Navel Of Day Old Chicks. Res. Journal of Microbiol, Vol.2, pp.960-965.

[10] Kamath, J.V., Rahul, N., Askok Kumar C.K. and Lakshmi, S.M. (2008): Psidium Guavaja L: A review. Int J. Green Pharm, Vol.2, pp.9-12.

[11] Khan, M.R., Omoloso, A.D. and Barewai, Y. (2006): Antimicrobial activity of Maniltoa schefferi extracts. Fitoterapia, 77, Iss.4, pp.324-326.

[12] Kilani, A.M (2006): Antibacterial Assessment of Whole Stem Bark of Vitex Doniana against some Enterobacteriaceae. African Journal Biotechnology, Vol.5, No.10. pp.958-959.

[13] Kunle, O.F and Egharevba, H.O (2009): Preliminary studies on Vernonia Ambigua: Phytochemistry and Antimicrobial Screening of The Whole Plant. Ethnobotanical leaflet, Vol.13, Iss.10, pp.1216-1221.

[14] Ntiejumokwu, S. and Alemika (1990): Antimicrobial and Phytochemical Investigation of Stem Bark of Boswellia Dalzielli. West African Journal of Pharmacology and drugs research, Vol.9, No.10, pp.1-2, p.6, p.101.

[15] Ogundare, A.O. (2007): Antimicrobial Effect of Tithonia Diversifolia and Jatropha Gossypifolia Leaf Extracts. Trends in Applied Sciences Research, Vol.2, No.2, pp.145-150.

[16] Oladunmoye, M.K. (2006): Comparative Evaluation of Antimicrobial Activities and Phytochemical Screening of Two of Acalypha Wilkesiana. Trends Applied Sci Res, Vol.1, Nol.1, pp.538-541.

[17] Osghae, F. and Omeregbe, R. (1977): Antimicrobial Activity of Extracts of Monordica Charantia. Journal of biotechnology, Vol.8, No.1, pp.30-32.

[18] Prescott, L.M., Harley, J.P. and Klien, D.A. (2005): Pathogenesis and Drug Resistance of Salmonella Typhi. Microbiology. 6th Edi. McGraw-Hill Companies Inc. York. Pp.780-792.

[19] Sofowora, E.A. (1988): Medicinal plants and traditional medicine in Africa. John Willey and Sons Limited, Chechester.

[20] Sofowora, E.A. (1993): The State of Medicinal Plants Research in Nigeria, Society of pharmacology, pp.54-96. [21] Soowora, E.A. (2003): Medicinal plants and traditional medicine in Africa. 2nd Edn, spectrum book Ltd

Nigeria. pp.63-78. [22] Tona, L., Kambu, K., Ngimbi, N., Mesia, K., Penge, O., Lusakibanza, M., Cimanga, K., De Bruyne, T., Apers, S.,

Totte, J., Pieers, L., Vienck, A.J. (2000): Antiamoebic and Spasmolytic Activities of Extracts From Some Antidiarrhoeal Traditional Preparations Used in Kinshasa, Congo, Phytomedicine, Vol.7, No.1, pp.31-38.

GLOBAL ENGINEERS & TECHNOLOGISTS REVIEW www.getview.org

G.L.O.B.A.L E.N.G.I.N.E.E.R.S. .& .-.T.E.C.H.N.O.L.O.G.I.S.T.S R.E.V.I.E.W 6

HAERYIP SIHOMBING1, HAFIZ2, M.K., YUHAZRI3, M.Y., KANNAN4, R.

1, 3 Faculty of Manufacturing Engineering Universiti Teknikal Malaysia Melaka

Hang Tuah Jaya, 76100 Durian Tunggal, Melaka, MALAYSIA [email protected] [email protected]

2, 4 Faculty of Mechanical Engineering

Politeknik Merlimau Melaka Pejabat Pos Merlimau, Melaka MALAYSIA

1.0 INTRODUCTION According to Adam et al., (1986), quality is the degree to which a product or service conforms to a set of predetermined standards, especially to the characteristics that determine its value in the market and its performance of the function to which it was designed. Based on this reason, quality is the result of a comparison between what was required and provided which it can be different things to different people and taken into account of both objective and subjective interpretations against the needs and expectations of customers (Chartered Quality Institute, 2012). When it is related to products, Meirovich et al., (2007) underlined that the quality is, in facts, the degree to which a product or service’s design (specification) fits to customer needs and expectations. While the conformance to quality is related to the degree of how match between the features of a specific product (service) to its specification. This is why the customers’ expectation involves the specification as a quality of product or service. And also the comparison against the competitors in the marketplace as which Prat and Tort (1989) in their study discusses why the pet food manufacturing companies need to implement the quality improvement as crucial task in order to survive in today’s marketplace.

Based on this consideration, if the improvement tasks and programs made are mainly in reducing the variability as well as other failure of products through the inspection in order to maintain economic viability, the facts that by such controlling conducted to the quality of product is, certainly, risked with the cost consumed (Jurans’ appraisal and failure cost). This is due to since a product must be efficient to manufacture and insensitive to variability on the factory floor and in the field, the business or company should therefore focus their concern through the development of extensive carefully planned experimentation at the design stage of products or processes. On this, by employing design of experiments (DOE) of the quality engineering methods proposed by Dr. Taguchi as one of the most important statistical tools of TQM for designing high quality, according to Unal and Dean (1991), will minimizing the process variation and reducing rework, scrap and the need for inspection systems at reduced cost.

In addition, although Design of Experiments (DOE) is the method related to experiment in terms to define the systematic procedure carried out under controlled conditions in order to discover an unknown effect, Genichi Taguchi developed this concept to improve the quality of manufactured goods based on the concept of "Uniformity around a target value." Related to this perspectives, Antony (2002) reported about the successful application of Taguchi method by many US and European manufacturers over the last 15 years in order to improve their product quality and process performance. This is due Taguchi concert off-line quality control based on an understanding of the loss function, system design, parameter design and tolerance design, that

ABSTRACT

The purpose of this study is to optimize the manufacturing process of the SME bread product using Taguchi method. The study is focused on the quality problems occurred as the outcomes of the process (quality of the bun produced) related to controllable factors of products design identified (machine temperature and length duration time) for the improvement required. By implementing the technique of analysis of variance (ANOVA), the composition of the controlled parameters, such as machine temperatures and duration times, is therefore determined and constructed into Orthogonal Array (OA) of L9(33) related to what the setting parameters produces the optimal output. To improve the quality of the manufactured product, the setting of parameter recommended in this study is A2B2C2 or A1B2C2 {(Low or High) ∩ 10minutes ∩ 200OC)}. Keywords: Taguchi method, Bread Manufacture, Loss Function, S/N Ratio.

TAGUCHI’S QUALITY IMPROVEMENT ANALYSIS OF THE SME BREAD MANUFACTURING



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enables the product development process is immediately produces a quality product or process at the lowest possible cost and thus the online quality control function during manufacturing and service after the sale effort are therefore reduced.

In facts, in the Small and Medium Enterprise (SME) food manufacturing where the manufacturing process runs in the traditional ways (Dhungana, 2003) and (Zulkifly et al., 2000), the varieties quality of products are always occurred. There are also found the limited implementation of management system and quality control towards the product to meet the specification, beside the lack of skill and knowledge operators. In facts, the problems occurred and found in this study are mostly due to setting the parameter of the machine to meet the specification of the end product. Since the company runs their production system solely depend on the visual inspection method to confirm the specification of end product (decision to finish the process of the bread cooking), then this condition effect to inconsistently quality of food products. Some of them are even overcooked or incomplete cook. Based on this reason, this study is carried to identify the parameter factors that affects to the quality of food manufacturing process and to determine the optimal parameter factors of food manufacturing process by using Taguchi Method. 2.0 LITERATURE REVIEW

2.1 DOE Using Taguchi Sukthomya and Tannock (2005) stated that Taguchi (1986) introduced a simplified and modified DOE approach which has been widely adopted by industry. This is due to Taguchi method is a technique for designing and performing the experiments to investigate the processes (where the output depends on many factors such as variables and inputs), without having to slow and uneconomically run the process caused by all possible of combinations values (Dobrzañski et al., 2007). Taguchi formulated both a philosophy and methodology for the process of quality improvement that depends on statistical concepts, especially statistically designed experiment. On this, the concept design is considered to be the first phase of the design strategy. This phase gathers the technical knowledge and experiences to help the designer to select the most suitable one for the intended product (Bharti and Khan, 2010).

Refer to American Supplier Institute (1992), Taguchi developed an approach to design of experiments that addressed the realities of industrial design, productivity and cost effectiveness based on the relationship between technology, variation, cost and savings. Since the classical experimental design methods are time consuming where the experiments must be performed when the number of control factors is high, Taguchi methods use a special design of orthogonal arrays to study the entire facto space with only a small number of experiments (Bharti and Khan, 2010).

The development of Taguchi’s method is based on orthogonal arrays (OA) related to statistics (Weng et al., 2007). Orthogonal Array (OA) is one part of the experimental group who only use part of the state total, where this section perhaps only half, quarter or an eighth of a full factorial experiment. An optimal experimental design should provide maximum amount of information by means of minimum experimental trials (Boran and Hocalar, 2007). Chong et al., (2009) stated that Orthogonal Array (OA) is a statistical DOE that is mostly applied in the manufacturing quality control and rapid software testing for faults detection.

OA is the matrix of numbers arranged in columns and rows. The Taguchi method employs a generic signal-to-noise (S/N) ratio to quantify the present variation. These S/N ratios are meant to be used as measures of the effect of noise factors on performance characteristics. S/N ratios take into account both amount of variability in the response data and closeness of the average response to target. There are several S/N ratios available depending on type of characteristics: smaller is better, nominal is best (NB) and larger is better. Refer to Cheng (2001), Taguchi has tabulated 18 basic orthogonal arrays that known as the standard orthogonal arrays. Each orthogonal array uses a notation that indicates its number of rows and columns, as well as the number of level in each column.

2.2 Manufacturing System Today, the earliest forms of bread would have been very different from how we can see in industrialized countries and it would probably be closest in character to the modern flat breads of the Middle East (Cauvain, 1999). The common process of producing breads is mainly based on 3 steps: dough formation, fermentation, and baking. 2.2.1 Dough formation

This process requires the mixing of flour, water, yeast, salt and other ingredients. On this process, the changes are associated with the formation of gluten, which requires both the hydration of the proteins in the flour and the application of energy through the process of kneading. According to



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Cauvain (1999), kneading is the development of gluten structure in the dough through the application of energy during mixing. Mixing the dough provides two functions: homogeneous distribution of components, and development of the gluten matrix. Gluten is the skeleton of wheat-flour dough and responsible for gas retention which provides the production of light loaf of bread. Mixing time varies with the flour, dough temperature, dough consistency, and mixer. 2.2.2 Fermentation Duration of the fermentation process depends on the amount and the quality of the ingredients. Yeast is the most important ingredient that affects the fermentation process. The relationship between dough development time and yeast level probably comes from the contribution that enzymes present in the yeast cells, viable or dead. They modify the protein structures, which are forming with increasing dough resting time. Flour also contains enzymes, which can contribute to dough development. Since the mechanism for dough development in fermentation depends on yeast activity, the temperature of the dough play a major role in determining the time at which full development is achieved (Cauvain, 1999). 2.2.3 Baking process During baking several changes take place both in the crumb and crust. The browning reaction that involves both ‘caramelization’ of sugars and ‘proteinaceousmaterials’ imparts a deep color to the crust. Thermal decomposition of starch and formation of ‘dextrins’ contribute to crust brightness. This is accompanied by formation of flavor and taste components. At the same time changes take place inside the loaf of bread. At early stages, the increase in temperature will enhances enzymatic activity and growth of yeast and bacteria. At about 50OC-60OC, the yeast and bacteria are killed. While on beyond temperature starch gelatinizes, proteins coagulate, and enzymes are inactivated. Steam is formed at around 100ºC, at which the final volume and crumb texture of the bread are set. The inside of the loaf does not exceed 100ºC; however, in the crust much higher temperatures are attained. In the temperature range of 100-150ºC, light and brown dextrin are formed which are followed by caramel (Pomeranz, 2004).The bread is allowed to cool at room temperature and ready for packaging. Figure 1 show the sequence production process in manufacturing bread.

Process 1

Mixing breaded Process 2

*Dough cutter Process 3

Steam bread in fermenting box

Process 4 Cook in Infrared food oven

Figure 1: Process Machine (Flow) 3.0 RESULTS AND DISCUSSION The study is carried out to identify and analyze the manufacture products in the food manufacturing industry. The industrial visit is conducted to the factory for clearly understanding about the food process manufacturing; technically and practically, and to deeply knowing about the problems and factors affecting to quality. The purpose of the industrial visit is to observe and understand the current process of manufacturing system, product quality, and quality control system, while the information of food manufacturing process flow and the quality performance is gathered for analysis.



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3.1 Study on Current Manufacturing System This study is conducted on the current food manufacturing system against the characteristic behavior of the selected controllable parameters applied in the food manufacturing production line process. The flow process and the steps of manufacturing as described below.

To determine the relationship between the quality of manufactured product and visual control

parameter of production line, the data collected is analyzed using Minitab software. By carrying out the experiment related to the process of control parameter design, the quantity, and location of reject items are identified and recorded, where a step plan used is to analyze results and implement solutions (Antony et. al., 2001).

3.2 Experiment Flow Process The experiment is carried out with several of the process which beginning of mixing flour until finishes cooking. The process flow of the production of the bread are illustrate in Table 1.

3.3 Bread Inspection The declaration of the bread inspection is based on the visual inspection on the surface of the bread. The inspection is doing manually for the appearance of the final product to confirmed the bread is acceptable and can be through the next process, packaging. The color of the bread (complete cook) and surface peak of final product are the measurable quality characteristics of this project. There are other characteristics that can be measured, but both of the above quality characteristics are considered for the most important criteria of market products by consumers. The table 2 shows the accepted and rejects condition for quality characteristics of the bread.

Values of quality characteristics (color of bread surface and surface peak of products) are affected by the conditions during production process of bread products. Diversifying values of baking duration and baking temperature of samples and the speed mixing type of ingredients of samples significantly affected quality characteristics. For this experiment considered, the above conditions are the factors of the experimental procedure. Since the purpose of this experiment is the optimization of bread product process, any non-linear relationship was taken into consideration. Here, non-linear effects are to be studied and it is necessary to choose more than two levels for each factors (Antony et al., 2001). The control factors and levels selected are shown in the table 3.

The experimental procedure is carried out in a controlled environment, as the experiment conditions remained stable. This ensures that there is no impact on results from external factors and the only conditions during the experiment varied in their values are three control factors, that is, mixing type, baking duration and baking temperature of process varied in each experiment trial. The quantities of

1. The first step is the mixing of the ingredients to make the dough of the bread.

1. Process 1: Mixing breaded • This process evenly distributes the ingredients, develop

the gluten and to initiate fermentation • The machine has 3 alternative speeds scale. • To change the speeds, first turn off the motor, then move

the shifter handle to the desired speed. • Speed number 1 for slow speed is for heavy mixtures. In

many mixing operation, it is customary to start on speed number 1 and then change to a higher speed as the work progresses.

• Speed number 3 for fast speed is for light work as whipping cream, beating eggs and mixing thin batters.

2. Then, the prepared dough is divided into several amounts by using dough cutter machine.

3. The dough are then will arranged on the tray. The composition of the dough is properly arranged to make sure the dough will baked completely later.

2. Process 2: Dough cutter • This process is continued from the first process which

divide the dough to several quantity that needed with set up at the machine button.

• The capacity for one cycle process is 112 pcs. per min.

3. The dough which has been prepared on the tray will then on hold in the fermenting box to ensure the dough is steamed to maintain the dough.

3. Process 3: Bread fermenting box • The prepared dough is transferred to the fermenting box.

This is required to keep the bun in good condition, fresh before transfer to oven.

4. Next, the bread is baking in infrared food oven at several times according to the setting.

5. The bread is allowed to cool in room temperature and packaging for sell.

4. Process 4: Infrared food oven • This gas oven provide platform type revolving hot air oven

for cook process. The surround hot air in the oven is support the cook process for several trays of buns in the oven.



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ingredients remained stable for all samples, based on the recipe that used always the industry for production of particular bread product. Figure 2 shows the equipment used to conduct the experiment.

Table 1: Process flow of the production of the bread

No Process Picture Description No Process Picture Description 1 Mixing

flour Mixing include flour , egg and water

6 Place in the mold

The dough is placed on the mold and compress to fill the mold.

2 Select mixing type

Mixing type divide by 3 speed: i.1 = Low

ii.2 = Medium iii.3 = High

7 Divide the dough

The mold is inserting into dough divider machine and the dough will served follow the weight that measure previously.

3 Mixing dough

The ingredient is mixing until the served as dough

8 Rub margarine

The margarine is rub on the tray surface to avoid the bread stick with tray surface.

4 Rest dough

The dough is put on the table for 10 minute and cover by plastic to avoid contamination.

9 Arrange on tray and place dough in fermenting box

The dough is placed on the fermenting box around 1 hour for steam process.

5 Scales the dough

The dough is scales for measure the appropriate weight for divide the dough.

10 Cook in the infrared food oven

The bread is cook in the oven follow the set up that arrange.

Table 2: Quality Characteristics Condition of the Bread

Position Unripe Complete Cook Overcook Defect

TOP

BOTTOM

N/A

Table 3: Control factors and levels of the experimental design

Factor Labelled Level 1

Level 2

Level 3

Mixing Type (rpm) A 1 2 3 Baking Duration (min) B 7 10 13

BakingTemperature (oC) C 195 200 205



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3.4 The L9 Orthogonal Array Experiments An Orthogonal Array (OA) is a matrix of numbers arranged in rows and columns. Each row represents the levels of the selected factors of a given experiment and each column represents a specific factors whose effects on the output. An OA help an experiments plans easily constructed by assigning factors to columns of the OA, then matching the different symbols of columns with the different factor levels. OA have the balanced property that every factor setting appear the same number of times for every setting of all other factors in the experiments.

In this research, the L9 (33) OA as shown in Table 4 is selected for the controllable factors since it is the most efficient orthogonal design to accommodate three factors at three levels. The L9(33) array specifies nine experimental run to be performed. This means that nine experimental trials with different combinations of the factors should be conducted in order to study the main effects. Three controllable factors is identified which could affect the quality of the bread manufacturing process. There are three parameters with three levels each. The three controllable factors parameters which selected are mixing type, baking duration (min) and baking temperature (OC). It is decided to test each controllable factor at three levels (Table 5).

The sequence in which the experiments were carried out was randomized to avoid any kind of

personal or subjective bias which may be conscious or unconscious. The Table 6 shows the combination of process variables for all nine experiments that have been run.

Table 6: Taguchi L9 (33) orthogonal array design

Experiment Trial

Parameters Mixing

type Baking duration

(min) Baking temperature

(oC) 1 Low 7 195 2 Low 10 200 3 Low 13 205 4 Medium 7 200 5 Medium 10 205 6 Medium 13 195 7 High 7 205 8 High 10 195 9 High 13 200

Table 4. Experiment layout using L9 (33) orthogonal array

Experiment Trial Parameters A B C

1 1 1 1 2 1 2 2 3 1 3 3 4 2 1 2 5 2 2 3 6 2 3 1 7 3 1 3 8 3 2 1 9 3 3 2

Table 5: Selected process parameters and their respective levels in experimental design

Process Parameters Symbol Level

1 (Low) 2 (Medium) 3 (High)

Mixing type A Low Medium High Baking duration (min) B 7 10 13 Baking temperature (oC) C 195 200 205



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No Equipment (machine) Picture Specification

1. Mixing machine

Model GF-201 Power (hp) ½ Bowl Capacity (liter) 20 Flour Capacity (kg) 3 kg Speed (rpm) 46/ 150, 88/ 316, 154/ 505 Gross Weight (kg) 120 (90 net) Dimension (mm) 550 x 500 x 840

2. Dough divider

Model HDD-36 Capacity (pcs) 36 Power (kw) 1.5 Voltage (v / hz) 240 / 50 Dividing Weight (g) 30 ~ 100 Weight (kg) 200 Dimension (mm) 520 X 420 X 1400

3. Fermenting box

Model FX-11 Layer 11 Power (Kw) 2.5K Voltage (v) 240 Weight (kg) 48 Dimension (mm) 500 x 755 x 1620

4. Infrared oven

Model GR-6 Gas Pressure (Pa) 2800 Heat Load (mj / hr) 135 Voltage (v / hz) 240 / 50 Weight (kg) 480 Dimension (mm) 1355 x 800 x 1780

Figure 2: The list of equipment used for experiment 4.0 DATA AND DISCUSSIONS The result of bread manufacture processes in this experiment is based on mean value of four samples at each set of experimental conditions for each process parameter variable. Table 7 shows the summarized result and it is found that experiment number 4 is the best combination control factor since the quantity of manufactured bread is greater in total accepted product.

4.1 Signal-to-Noise Ratio The Taguchi’s method provides the orthogonal array as a mathematical tool that allows the analysis of the relationship between a large numbers of design parameters by using only a limited number of experiments run. The target based on the conditions identified which resulting the optimal process or product performance. Here, the S/N ratio is the Taguchi advocates for measuring the quality through orthogonal array based experiments. The S/N ratio is used to convert the trial result data into a value for the evaluation characteristics as the optimum setting analysis.

In this study, the visual inspection against the output is to determine the quality characteristics considered of the bread product. To analyze and determine which the optimal parameter factors for the bread manufacturing process, the reject should be in minimum as the acceptable of output.



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Table 7: Summarized results of manufactured bread quality (See Appendix)

Experiment Trial

Total accepted

Reject Total

Unripe Defect Overcook 1 12 3 0 0 3 2 13 0 2 0 2 3 0 0 0 15 15 4 14 1 0 0 1 5 15 0 0 0 0 6 7 0 3 5 8 7 11 0 4 0 4 8 11 0 3 1 4 9 12 0 0 3 3

The S/N ratio selected for this study is larger-the-better quality characteristics. The calculation and equation for S/N ratio is as following:

4.1.1 Larger- the- better:

S/N = -10 log (∑(1/yi2) / n)

Where, yi = each observation value n = number of observation (values at each trial condition)

The result is as Table 8.

Table 8: Calculation for S/N ratio (Larger-the-better)

n y y2 S/N ratio 1 3 9 21.5836 1 2 4 22.2789 1 15 225 undefined 1 1 1 22.9226 1 0 0 23.5218 1 8 64 16.9020 1 4 16 20.8279 1 4 16 20.8279 1 3 9 21.5836

4.1.2 Main effect of signal-to-noise ratio (S/N) response The main effect plot is a plot of the mean response values at each level of design parameter or process variables. The sign of the main effect indicates the direction of the effect, whether the average response value is increases or decreases. The magnitude indicates the strength of the effect. If the effect of a design or process parameter is positive, it implies that the average response is higher at high level then at low level of the parameter setting. In contrast, if the effect is negative, it is means that the average response at the low level setting of the parameter more than at the high level.

4.1.3 Main effect plot for signal-to-noise ratio Figure 3 shows S/N graphs for the bread manufactured experiment respectively. Basically, the larger the S/N ratio shows the better the quality. Based on this graph, it reveals that the trend of the mixing type is less significant than other factors. The S/N ratio is slightly decreased from low setting to medium setting, but the S/N ratio is slightly increased and approach to the mean line for high type of mixing setting. For baking duration, the graph trend begins with slightly increased between 7 minute and 10 minute of baking process. The S/N ratio value between 10 minutes and 13 minutes is squally decreased and approach to the minimum of the S/N ratio value. For baking temperature, the S/N ratio is smoothly increased between 195 oC and 200 oC and approach to the maximum of S/N ratio which then followed by slightly decreased of baking temperature of 200 oC to 205 oC. Based on the Figure 3 and Table 9, it can be describe that the baking duration is the main factor influenced to the quality of the output of the bread manufacturing process. It shows that the baking duration is the control factor that has the most significant factor. The effect of the other factors (A and C) is of less significance.

Table 9 shows the average S/N ratio values for the experiment at three levels setting of each factor and the effect of each main effect on the S/N ratio in respectively. The mean of S/N ratio for percentage of the mixing type at level 1, level 2 and level 3 is 26.82, 26.40 and 26.48 in respectively.



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Clearly, the S/N ratio of mixing type at level 1 appears to be the best choice since it corresponds to the highest average S/N ratio. The mean S/N ratio of baking duration is 26.75, 26.92 and 25.62 at level 1, level 2 and level 3 in respectively. The S/N ratio for baking duration suggests that parameter at level 2 is better than at level 1 and level 3. Level 2 shows as the highest average of S/N ratio and is considered as the best choice. For S/N ratio of baking temperature, same as previous, level with highest S/N ratio will be chosen so; the best choice is at level 2 with 26.95. From the analysis above, the optimum parameters selected to optimize the quality of bread manufactured are A1B2C2.

The maximum-minimum value is equal to the range of S/N ratio variance due to the change in the level setting. The larger the range, the more powerful impact the control factor has on quality. The ranking in Table 10 show that S/N ratio of baking duration, which has ranking 1, has relatively strong impacts and influence on the quality of bread. S/N ratio of mixing type and baking temperature which has ranking 2 and 3 respectively have relatively weak impacts. So, S/N ratio of baking duration should be strictly controlled for high quality of bread during the manufacturing process.

Instead, Table 9 shows that the most significant factor for the output of the product is the control factor toward B (Baking duration). The effect of the other factors (A and C) is of less significant. Since the objective of this study is to optimize the bread product process, the S/N ratio should be maximal in order to minimize variability. Thus, factor B should be to set at level 2 in order to get the maximum result.

4.1.4 Main effect plot for means Figure 4 shows the mean graphs for the bread manufactured experiment. Basically, the larger of the S/N ratio is as the better of quality. Figure 4 shows the best levels for each control factors to obtain the optimal accepted of the bread product. Based on the graph, it shows that the trend of the mixing type is less significant compared to other factors. The mean is slightly decreased from low setting to medium setting, but then slightly increased by approaching the mean line for high type of mixing setting. For baking duration, the graph trend begins with slightly increased between 7 minute and 10 minute of baking process. The mean value between 10 minute and 13 minute is squally decreased by approaching the minimum of the S/N ratio value. For baking temperature, the mean is smoothly increased between 195oC and 200oC by approaching the maximum of mean and follow by slightly decrease for baking temperature of 200oC to 205oC. From the Figure 4 and Table 10, it can be described that the baking duration is the main factor that influence the quality of the output of the bread manufacturing process. It shows that the baking duration is the control factor that has the most significant factor. The effect of the other factors (A and C) is of less significance.

Table 10 shows the average mean values for the experiment respectively at three levels setting of each factor and the effect of each main effect on the mean. The mean of mean values for the mixing type at level 1, level 2 and level 3 is 21.93, 21.12 and 21.08 in respectively. Clearly, the mean of mixing type at level 1 appears to be the best choice since it corresponds to the highest average mean. The mean of baking duration is 21.78, 22.21 and 19.24 at level 1, level 2 and level 3 in respectively. This is means that for the baking duration, the parameter at level 2 is better than at level 1 and level 3. Same as previously, the level with highest mean will be chosen as the best choice, which is 22.26.

Based the analysis above, the optimum parameters selected to optimize the quality of bread manufactured is A1B2C2. Since the maximum-minimum value is equal to the range of mean variance

HighMediumLow

27.0

26.5

26.0

25.513107

205200195

27.0

26.5

26.0

25.5

Mixing type

Mea

n o

f SN

rat

ios

Baking duration

Baking temperature

Main Effects Plot for SN ratiosData Means

Signal-to-noise: Larger is better Figure 3: Main effects plot for S/N ratio of experiment

Table 9: Response Table for Signal to Noise Ratios

Level Mixing

type A

Baking duration

B

Baking temperature

C 1 26.82 26.75 25.87 2 26.40 26.92 26.95 3 26.48 25.62 26.90

Difference (Max –Min) 0.42 1.30 1.08 Rank 3 1 2

*Higher value



15

due to the change in the level setting, the larger the range, the more powerful impact the control factor has on quality. The ranking in Table 11 shows that the baking duration has ranking 1 and relatively strong impacts and influence on the quality of bread. Thus, the mixing type and baking temperature are the ranking 2 and 3 where they are relatively give the weak impacts..

Table 10 shows that the most significant factor for the output of the product is control factor

B (Baking duration). The effect of the other factors (A and C) is of less significant. Since the objective of this project is to optimize the bread product process, what is required is to the maximum values in order to minimize variability. Thus, factor B should be to set to Level 2 in order to get the maximum result.

4.2 Analysis of Variance (ANOVA) The purpose of the ANOVA is to investigate and recognize which process have the significantly affects to the quality of the manufactured bread. From the analysis, it is used to identify which factors are the most important in terms of quality characteristic. Consequently, the important factors identified have to be properly monitored during the process for a consistently gather high quality of bread product.

The ANOVA analysis is performed by noting the sources of variation in the left hand column, which are the factors under the experiment. The description of the label in ANOVA analysis is as follow:

Table 11: List of ANOVA label

Label Description DOF Indicates degree of freedom for the factor SS Sum of square

- Squared deviation of a random variable from means. MS Mean square

- Sum of square dividing by the number of degree of freedom associated with the factors effects.

F Result of the traditional Fisher test for significance - Measure effect of each factor or interaction relative to the error.

P Indicates the percent contribution of each factor.

Table 12: ANOVA for S/N ratio

Factors DOF Seq SS Adj SS Adj MS F P Mixing type 2 0.2295 0.01016 0.00508 0.00 0.996 Baking duration 2 2.0408 1.40689 0.70345 0.50 0.707 Baking temperature 2 1.7530 1.75299 0.87649 0.62 0.667 Residual error 1 1.4064 1.40641 1.40641 Total 7 5.4297

Table 13: ANOVA for Mean

Factors DOF Seq SS Adj SS Adj MS F P Mixing type 2 1.044 0.00505 0.00252 0.00 1.000 Baking duration 2 10.600 7.20890 3.60445 0.48 0.713 Baking temperature 2 9.394 9.39395 4.69697 0.63 0.665 Residual error 1 7.436 7.43794 7.43794 Total 7 28.477

HighMediumLow

22

21

20

1913107

205200195

22

21

20

19

Mixing type

Mea

n of

Mea

ns

Baking durat ion

Baking temperature

Main Effects Plot for MeansData Means

Figure 4: Main effects plot for Data Means of experiment

Table 10: Response Table for Means

Level Mixing

type A

Baking duration

B

Baking temperature

C 1 21.93 21.78 19.77 2 21.12 22.21 22.26 3 21.08 19.24 22.17

Difference (Max –Min) 0.85 2.97 2.49 Rank 3 1 2

*Higher value



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At the end of the experiment, the result shows that the combination of parameters factors produce the different output of the bread manufacturing process. The influences of the combination carried out are illustrated in Figure 5 for all of 9 experimental trial, where the defects detected at the each of the matrix array location on the tray. It shows that the most high defect area is at the b3 and c3 area which consist of 5 defects. The area of b1 and c1 as the second highest defects area with 4 defects occurred during the experiment. From the experiment of factor arrangement in orthogonal array (OA), the location of the defects related to the combination of setting parameter factor, such as mixing type, baking duration and baking temperature identified. It is found that the highest of defects area occurred at the 2, 3, 6,7,8,9 arrangement number of experiment trial.

Figure 5: Bread location for overall experiment trials

Based on the combination parameter factors, it is found that the setting parameter of L-H-H , M-H-L and H-L-L are having greater influences to the rejected output at the critical location (b3 and c3). Since the specific location found as the repeatable defects location, the further study required is by analyzing the influence of the heat transfer in the oven that may affect the quality of the bread.

5.0 CONCLUSION In this project, the mixing type, baking duration and baking temperature is identified as the parameter factors that affects to the quality of food (bread) manufacturing process. The analysis using Taguchi‘s method shows that the optimal result achieved when the parameter setting of the process is A1B2C2. This is means that the mixing type should set to low, baking duration at 10 minutes and baking temperature at 200 0C. This optimum process of controlled parameters setting indicated that the baking duration is as the most significant factor. Since the measurement of the bread quality characteristic in this study is determined by visual inspection, the development method to inspect the taste, weight, surface peak, shape, texture or structure of bread products are also required for further study. In addition, the further study required is against the heat transfer distribution of the oven that is influenced by location of heat generator (microwave) towards the objects. ACKNOWLEDMENTS The authors would like to thank CRIM-UTeM. This project is supported by CRIM through PJP/2011/FKP (11D) S00878. REFERENCES [1] Adam, E.E., Jr., Hershauer, J.C. and Ruch, W.A. (1986): Productivity and Quality: Measurement as a Basis for

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[13] Meirovich, G., Brender-Ilan, Y., and Meirovich, A. (2007): Quality of Hospital Service: The Impact of Formalization and Decentralization. International Journal of Health Care Quality Assurance, Vol. 20 No.3, pp.240-252.

[14] Pomeranz, Y. (1987): Modern Cereal Science and Technology. VCH Publishers, USA. ,pp.248-249 [15] Prat, A. and Tort, X. (1989): Case Study: Experimental Design in A Pet Food Manufacturing Company.

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[16] Simpson, T.W., Wysk, R. A., Niebel, B.W. and Cohen, P.H. (2000): Manufacturing Processes: Integrated Product and Process Design. New York: The McGraw-Hill Companies, Inc.

[17] Sukthomya, W. and Tannock, J.D.T. (2005): Taguchi Experimental Design for Manufacturing Process Optimisation using Historical Data and a Neural Network Process Model. International Journal of Quality & Reliability Management, Vol. 22 No. 5, pp.485 – 502.

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[20] Weng, W.C., Yang, F. and Elsherbeni, A. (2007): Electromagnetics and Antenna Optimization Using Taguchi’s Method. Synthesis Lectures on Computational Electromagnetics, Vol. 2, No. 1 , pp. 1-94.

[21] Zulkifly, M.I., Mohd Zahari, M.HJ., Jalis, M.H., and Othman, Z. (2010): An Investigative Study into the Hazard Analysis of Critical Control Point (HACCP) Implementation in Small and Medium-Sized Food Manufacturing Enterprises (SMEs). Journal of Tourism, Hospitality & Culinary Arts, Vol.1, No.3, pp.101-112.



18

APPENDIX

Expe

rim

enta

l Tr

ials

Mix

ing

Ty

pe

Baki

ng T

ime

D

urat

ion

(min

)

Baki

ng

Tem

pera

ture

(oC)

Quality Characteristics (Surface Inspection)

Picture Total

Tray Qty

1 L L L

a1 b1 c1 ov 0

TOV 0 a2 b2 c2 rp 3 TRP 3 a3 b3 c3 df 0 TDF 0 a4 b4 c4 td 3 TD 3 a5 b5 c5 ta 12 TA 12

2 L M M

a1 b1 c1 ov 0


3 L H H

a1 b1 c1 ov 15


4 M L M

a1 b1 c1 ov 0


5 M M H

a1 b1 c1 ov 0


6 M H L

a1 b1 c1 ov 5 TOV 5 a2 b2 c2 rp 0 TRP 0 a3 b3 c3 df 3 TDF 3 a4 b4 c4 td 8 TD 8 a5 b5 c5 ta 11 TA 7

7 H L H

a1 b1 c1 ov 0 TOV 0 a2 b2 c2 rp 0 TRP 0 a3 b3 c3 df 4 TDF 4 a4 b4 c4 td 4 TD 4 a5 b5 c5 ta 11 TA 11

8 H M L

a1 b1 c1 ov 1

TOV 1 a2 b2 c2 rp 0 TRP 0 a3 b3 c3 df 3 TDF 3 a4 b4 c4 td 4 TD 4

a5 b5 c5 ta 11 TA 11

9 H H M

a1 b1 c1 ov 3


No 1-1, Jalan KNMP 2A, Kompleks Niaga Melaka Perdana,

75450, Ayer Keroh, Melaka, MALAYSIA.