Die evaluering van die produksievloei by 'n jogurtfabriek in Suid-Afrika
Date
2022-04
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
Stellenbosch : Stellenbosch University
Abstract
AFRIKAANSE OPSOMMING: Jogurt is ‘n bederfbare produk en uiters sensitief vir tyd, temperatuur en hantering. Hoe langer dit neem om die produk te vervaardig, te verpak en te versprei, hoe groter is die kans vir beskadiging en terugsendings. Daar is ook verskeie kostes verbonde aan die stoor van die produk terwyl dit afkoel en wag om versprei te word.
Die betrokke maatskappy wil ‘n groter fokus op intydse verskaffing plaas. Om die vlak van
intydse verskaffing te verbeter, moet produkte so vinnig en effektief as moontlik deur die fabriek
beweeg. Produkte wat vinniger deur die fabriek beweeg het ‘n laer drakoste, skep nuwe
stoorspasie vir ander produkte en verlaag die risiko van terugsendings. Kwalitatiewe data is ingesamel deur verskeie gesprekke met die produksiebestuur, koelkamerbestuurder en bedryfshoof te voer. Kwantitatiewe data is ingesamel deur observasies in die fabriek self. Jogurtprodukte se verpakkingstye is geneem en die produkvloei is gedokumenteer. ‘n Diskrete gebeurtenis simulasiemodel is ontwerp en gebou om die stasies in die fabriek voor te stel. Die model se uitslae is gemeet deur drie prestasiemaatstawwe met mekaar te vergelyk, naamlik hantering, tyd en ledigheid. Hierdie uitslae is met sewe alternatiewe scenario’s, waar
veranderinge aan die stelsel gebring is, vergelyk. Hierdie scenario’s sluit klein veranderinge in
soos om robotte aan die einde van twee lyne te installeer en die werkers te verminder, sowel
as om ‘n toedraaimasjien in die verpakkingsarea te voeg. Dit sluit ook groter veranderinge in
soos om die toedraai-aanleg te skuif na ‘n ander area in die fabriek en om blaasvrieskaste in die
koelkamers te installeer. Produkte word in twee kategorie¨e verdeel na aanleiding van die preserveermiddels wat by die jogurt gevoeg word. Twee metings, tyd in die koelkamer en tyd in die stelsel (wat die koelkamers en verpakking insluit), word gebruik om die model te evalueer. A-produkte spandeer ongeveer 433 minute in die koelkamers en 458 minute in die stelsel. B-produkte spandeer ongeveer 1401 minute in die koelkamers en 1458 minute in die stelsel. Die hoofdoel van die studie, sowel as van die maatskappy, is om die tyd wat produkte in die
fabriek spandeer, te verminder. Die scenario wat die beste uitslae gelewer het, was om blaasvrieskaste
in die koelkamers te installeer. Dit kan daartoe lei dat produkte wat die oggend gepak is, dieselfde dag nog versprei kan word en produkte wat tydens die nagskof gepak word, die volgende oggend gereed sal wees vir onmiddellike verspreiding. Blaasvrieskaste kan besparings van meer as 50% in die tyd wat produkte in die stelsel spandeer, teweeg bring. Die installering van ‘n toedraaimasjien by die verpakkingstasies is die tweede beste scenario. Hier kan die hantering van die produkte, sowel as die arbeidsmag, verminder word. Dit impliseer dat
produkte dadelik nadat primˆere en sekondˆere verpakking plaasgevind het, toegedraai kan word
en gereed is vir verkoeling. Wanneer hierdie produkte eers na die toedraai-aanleg geneem moet word, vind dubbele hantering plaas. Hierdie hantering impliseer ekstra arbeid en ekstra tyd op die produk se tydstempel. Die ledigheid van werkers verbeter effens tydens die eerste twee scenario’s wanneer robotte en ‘n toedraaimasjien in die verpakkingsarea ge¨ınstalleer word. Werkers kan egter beter benut word deur die aktiwiteite op die lyne s´o te skeduleer dat dieselfde werkers op verskillende lyne gebruik kan word.
ENGLISH SUMMARY: Yogurt, a perishable product, is, amongst other things, sensitive to time, temperature and the handling thereof. The longer it takes to produce, pack and distribute the product, the greater the chances are of it being damaged or sent back. Other costs like carrying costs are also influenced by the time these products spend in the factory. The chosen company wants to focus on just-in-time delivery. To increase their level of just-intime delivery, products need to move through the factory as fast and efficient as possible. Faster moving products have less carrying costs, create more space for other products and minimise the risk of returns. Qualitative data is gathered through conversations with the production manager, the cold room manager and the chief operating officer. Quantitative data is gathered by observations in the factory by measuring the packing times of the yogurt containers and documenting the product flow. A discrete event simulation model is designed and built to represent all the different stations in the factory. The results of the model are measured by the three performance indexes: handling; time; and idleness, and compared among seven different scenarios where changes are made to the existing model. These scenarios include small changes like adding a packing robot at the end of two lines and decreasing the number of workers, and adding a wrapping machine in the packing area. It also includes bigger changes like moving the wrapping plant to a different place in the factory and installing blast freezers in the cold rooms. Because of preservatives, products are divided into two divisions. Two measurements, time in the cold rooms and time in system (which includes the cold rooms and the packing area) are used to evaluate the different models. A-products spend on average 433 minutes in die cold rooms and 458 minutes in the system, while B-products spend an average of 1401 minutes in the cold rooms and 1458 minutes in the system. The main goal of this study, and of the company, is to shorten the time products spend in the factory. The scenario which performed the best was when blast freezers are installed in the cold rooms. Products can leave the same day when packed in the morning and the next morning when packed during the night shift. This can save more than 50% of the time products spend in the factory. The second best scenario is to install a wrapping machine in the packing area, which can lower handling of the products, as well as reducing the number of workers needed to wrap the products. This will ensure that products are wrapped immediately after packed in primary and secondary packaging and will eliminate the process of initial wrapping, moving to the wrapping plant, depaletising the products, wrapping of the individual products and paletising it again. Although the idleness of the workers improve slightly in Scenarios 1 and 2 (installation of the robots and the wrapping machine in the packing area), the idleness of the workers would only truly improve if scheduling of the same workers on different lines would take place. If activity on the lines are scheduled in such a way that workers can be shared amongst lines, the best results will be achieved.
ENGLISH SUMMARY: Yogurt, a perishable product, is, amongst other things, sensitive to time, temperature and the handling thereof. The longer it takes to produce, pack and distribute the product, the greater the chances are of it being damaged or sent back. Other costs like carrying costs are also influenced by the time these products spend in the factory. The chosen company wants to focus on just-in-time delivery. To increase their level of just-intime delivery, products need to move through the factory as fast and efficient as possible. Faster moving products have less carrying costs, create more space for other products and minimise the risk of returns. Qualitative data is gathered through conversations with the production manager, the cold room manager and the chief operating officer. Quantitative data is gathered by observations in the factory by measuring the packing times of the yogurt containers and documenting the product flow. A discrete event simulation model is designed and built to represent all the different stations in the factory. The results of the model are measured by the three performance indexes: handling; time; and idleness, and compared among seven different scenarios where changes are made to the existing model. These scenarios include small changes like adding a packing robot at the end of two lines and decreasing the number of workers, and adding a wrapping machine in the packing area. It also includes bigger changes like moving the wrapping plant to a different place in the factory and installing blast freezers in the cold rooms. Because of preservatives, products are divided into two divisions. Two measurements, time in the cold rooms and time in system (which includes the cold rooms and the packing area) are used to evaluate the different models. A-products spend on average 433 minutes in die cold rooms and 458 minutes in the system, while B-products spend an average of 1401 minutes in the cold rooms and 1458 minutes in the system. The main goal of this study, and of the company, is to shorten the time products spend in the factory. The scenario which performed the best was when blast freezers are installed in the cold rooms. Products can leave the same day when packed in the morning and the next morning when packed during the night shift. This can save more than 50% of the time products spend in the factory. The second best scenario is to install a wrapping machine in the packing area, which can lower handling of the products, as well as reducing the number of workers needed to wrap the products. This will ensure that products are wrapped immediately after packed in primary and secondary packaging and will eliminate the process of initial wrapping, moving to the wrapping plant, depaletising the products, wrapping of the individual products and paletising it again. Although the idleness of the workers improve slightly in Scenarios 1 and 2 (installation of the robots and the wrapping machine in the packing area), the idleness of the workers would only truly improve if scheduling of the same workers on different lines would take place. If activity on the lines are scheduled in such a way that workers can be shared amongst lines, the best results will be achieved.
Description
Thesis (MCom)--Stellenbosch University, 2022.
Keywords
Dairy products -- Analysis -- South Africa, Yogurt industry -- South Africa, Dairy processing -- South Africa, Milk -- Processing -- South Africa, Food industry and trade -- South Africa, UCTD