1,720,986 research outputs found
A roadmap for improving the manifacture of automotive heat exchangers through value stream mapping
No full textSubmitted in fulfillment of the requirements of Master of Engineering, Durban University of Technology, Durban, South Africa, 2019.Lean manufacturing is an optimum approach for the reduction and elimination of waste within an organization. The case study company is based in South Africa and produces heat exchangers through main processes or fractals, which include pre-assembly, core building, brazing and final assembly. A walk through the plant showed that there was a large amount of inventory awaiting final assembly and that the brazing furnace often waited for material from core building. This was an indication that there could be an imbalance between the three fractals in terms of cycle time. Thus, the aim of this study was to improve the manufacturing processes for heat exchangers at the automotive manufacturing company through the deployment of value stream mapping, subsequent line balancing and developing a roadmap for reduction of waste. The case study research strategy was adopted for the study since it provided an in-depth view of phenomena.
The first objective was to outline the production flow for the manufacture of automotive heat exchanger parts. The method used was a walk through the plant and observations were made to gain an understanding of the production steps from logistics production planning to shipping of the finished goods, and subsequently to a mapping-out of the production process flow was undertaken. The results showed that there was a large amount of inventory awaiting final assembly and that the brazing furnace often waited for material from core building. It was concluded that there was need to conduct a detailed process analysis to identify sources of waste.
The second objective was to conduct value stream mapping for assessing the value- and non-value-adding activities in the manufacture of automotive heat exchangers components. A value stream map was developed through walking to Gemba and mapping out the production process, collecting data and pinpointing waste activities or areas to be improved. The kaizen flashes from the value stream map also revealed that operators were not fully utilizing the capacity of the bottleneck workstations. It was concluded that two instead of one planning points, and inefficiency at assembly were root causes of the high work-in-process level.
The third objective was to conduct a line balancing analysis for the three production fractals. The method used was a Pareto analysis for evaluating the products, analysing the product mix and line balancing analysis of the production line. The results revealed that the furnace was run on two shifts while the subsequent assembly and preceding core building were running on three shifts causing a work-in-process build-up, thereby resulting in line imbalance. It was concluded that it was imperative to change the scheduling approach, and adopt one that prioritised and spread the cores that had relatively short cycle times, and also reduce downtime, change-over time as well as additional time for scrap and defects, and a future-state balance chart revealed that the fractals imbalance had been reduced.
The fourth objective was to develop a roadmap for reduction of waste in the manufacture of car heat exchangers components. The method used was to develop proposals and assess the feasibility and cost implications of implementing each option.
Recommendations were made for continuous process improvement and a roadmap for reduction of waste was proposed. In order to improve the output of assembly, training for the operators was recommended since it would also enable the removal of the second planning point at assembly. Further research could also be conducted to develop an optimal scheduling algorithm for allocation of products to work centres to ensure high utilization of work centres and reduce work-in-process inventory.
Comparative analysis of the implementation of Toyota Production System between a tier-one and tier-two supplier
No full textSubmitted in fulfillment of the requirements for the Master of Engineering degree, Durban University of Technology, Durban, South Africa, 2024.The Toyota Production systems (TPS) is a methodology that is widely used in the manufacturing automotive industry. The Toyota pyramid model consists of four levels which can be dissected into the first level of philosophy, the second level named process, the third pillar of people and partners, and lastly the problem-solving level. These are also characterised by 14 principles of the model. However, many suppliers face challenges in implementing these principles from the Toyota pyramid model due to lack of knowledge, understanding or available framework for easy implementation and guidance. This study aims to conduct a comparative analysis of the level of implementation of the 14 principles of the Toyota pyramid model by a tier-one and tiertwo supplier. This study also identified areas of strengths and weakness and made provisions for continuous improvement initiatives at each supplier for future work. A quantitative research methodology with a questionnaire as the research instrument, was adopted for this study. A 5-point Likert type scale was used to elicit responses from 25 research participants from the tier-one and tier-two suppliers. Data analysis was conducted through descriptive values of the means, skewness and kurtosis, and an independent sample t-test was used as an inferential tool to establish the relationship between the tier-one and tier-two supplier. Value stream mapping was also deployed to identify the current production processes and kaizen bursts that characterized the two organisations. The results from the comparative analysis of the level of implementation of the Toyota pyramid model revealed that tier-one supplier was demonstrating better performance than tier-two supplier in the implementation of the 14 principles. In addition, the results demonstrated that principle 1, from the philosophy level had a higher mean or was stronger for each supplier. On the hand, principle 8 and principle 12 were found to be weaker in each supplier respectively. The areas of improvement which were highlighted in the kaizen bursts on the value stream map were addressed and kaizen implementation was undertaken. These improvement initiatives included rebalancing a seat-cover assembly line and deployment of an andon management system at the tier-one supplier to improve line efficiency and line management. A framework was also proposed for the tier-two supplier to bridge the gap in its practice for implementation of the Toyota pyramid model principles. Additional principles were added to this framework to ensure an easier and understandable methodology and framework to be referred to for suppliers and companies to improve.
Use of scientific ergonomic programs to improve organisational performance
No full textSubmitted in fulfilment of the requirements for the Master of Engineering degree, Durban University of Technology, 2021.The packaging industry is characterised by ineffective ergonomic programs that are
inadequately implemented thereby failing to yield benefits for the organisations. The
study aims to determine an effective scientific ergonomic program that focuses on
improving the organisation's overall performance by aligning these programs with the
organisation's business strategy. A quantitative research methodology with a
questionnaire as the research instrument was adopted for this study. A quantitative
analysis was conducted at two sites of a liquid packaging company in South Africa
using a sample of 70 participants from the production and engineering departments.
The data collected in this study were analysed with descriptive statistics.
The findings on the anthropometric and physiological factors revealed that the
employees at the packaging sites were generally satisfied with the workstation design.
However, it was found that several factors hindered the effective implementation of
ergonomics in the packaging industry, and these include awareness in the subject of
ergonomics, job task design, human-computer interaction, disconnection between
employees and organisational strategies and poor implementation of anthropometric
and physiological factors. The findings on the factors related to illumination also
revealed that the light reflections, shadows, or flicker from the fluorescent tubes could
be prevented. Additionally, a high percentage of the respondents also disapproved of
the current lighting conditions that need to be addressed to prevent any risk of injury
or poor performance related to lighting and illumination. The findings also
demonstrated that there was a need for an improvement plan concerning noise and
vibration at the packaging sites.
It was also found that there is a huge gap in knowledge about the basic principles and
fundamentals of ergonomics. While most workers understood their job expectations
none of them understood how factors such as safety procedures, operational
performance, and employee best practices fitted into the bigger picture of the
organisation. An effective ergonomic program that incorporated systems engineering
risk assessment methodology, was developed, embracing a probability of occurrence
matrix, ratings of criticality and rating of consequences. It was recommended that the
organisation should train employees on ergonomics best practices to create an effective program that will address operational gaps and enhance the organisation's overall performance.
Modernisation of fault detection for diagnosis routines in elevators
No full textSubmitted in fulfilment of the requirements for the degree of Master of Engineering: Industrial Engineering, Durban University of Technology, Durban, South Africa, 2018.Abstract
Maintenance of elevators has become critical in ensuring continued operation by preventing
excessive wear and breakdown. Maintenance greatly affects elevator downtime and uptime, hence
the need for modernising elevator maintenance to stay abreast of other competitors. This research
focuses on the modernisation of maintenance in elevator systems to reduce breakdowns through
scheduled maintenance via remote condition monitoring for fault detection using the Internet of
Things (IoT) technology. The monthly scheduled maintenance policy for the elevator system,
however, increased the downtime of the system due to lengthy response time to attend to elevator
breakdowns. This research therefore adopts remote monitoring of the elevator system’s condition
for early detection of malfunctioning and faults notification for a just-in-time maintenance
response.
The parameters which could indicate a fault, deterioration, or damage of the elevator system were
identified. The methodology embraced building and configuring an electronic monitoring device
which comprises of the sensors, LED light, a voltage source, breadboard, jumper wires and an IoT
microcontroller. The microcontroller is programmed to monitor temperature, 3 axial vibration, and
acoustics parameters of the elevator system. Data and fault notifications are sent to a registered
email for remote monitoring access on the cloud. The IoT devices and controller make use of any
back up system which can be accessed in the cloud as a secondary storage system for the data
being read by the sensors and notification updates. The back-up system used in this research is
electronic mail. The read data from the machine was posted, together with the fault notification in
cases of malfunctioning of the condition, to an email cloud server.
The results show that remote condition monitoring of the elevator system is a better maintenance
approach as it reduces the downtime of the elevator system through just-in-time fault notification,
trend monitoring for fault troubleshooting and also diagnosis of fault from historical events. This
is indicated by a considerable reduced response time, (81%) as compared to the initial state of the
system, with a total response time of 45.4 hours for the 6 fault notifications experienced during the
condition monitoring unlike 240 hours for 4 breakdowns before modernising the maintenance
approach. Five of the six breakdowns experience were indicated by both vibration and acoustics
parameters which shows they are complimentary in fault diagnosis. An optimised limit for each
parameter was also derived using control chart for variables analysis.
The impact of COVID-19 pandemic on supply chain performance : a case of an earth-moving equipment manufacturer
No full textSubmitted in fulfilment of the requirements of the degree of Master of Engineering, Durban University of Technology, Durban, South Africa, 2024.The COVID-19 pandemic impacted the supply chain performance of an earth-moving
equipment manufacturer in KwaZulu-Natal, South Africa. The pandemic damaged the
company's supply chain, causing material shortages and production problems which
made it difficult to satisfy customer demand. This research aims to maximize the supply
chain of an earth-moving equipment manufacturer in South Africa through the
identification and addressing of supply chain blockages that were created by the COVID19 pandemic. The study seeks to characterise the defining elements of supply chain,
identify factors affecting performance, apply value stream mapping for efficiency, and
develop a framework model for supply chain optimization. Ultimately, the study seeks to
address gaps in comprehending the long-term effects of the pandemic on earth-moving
equipment manufacturers' supply chains and propose strategies to build resilience
against future disruption. Quantitative approach was used to analyse forecast data
against actual deliveries to control productivity and delivery performance. Six Sigma,
cause-and-effect diagrams, and time studies methods were used to identify inefficiencies.
Supply change elements were characterised using Gemba walks and process flow
mapping, which provided direct observations of operations and visualizing interconnected
processes. Pareto analysis, cause-effect diagrams, value stream mapping, and time
studies were used for identifying supply chain performance issues, improving supply
chain efficiency, and recognizing waste and production blockages. Qualitative
observations and quantitative measurements of production processes were used for data
collection. The methodology provided a comprehensive insight into the supply chain
problems and areas to apply targeted improvements to increase efficiency and customer
satisfaction. Findings highlighted the importance of developing strategies including
diversification among suppliers, workforce development, logistics optimization, adoption
of digital technologies, and improvement in demand planning. The study also identified
that adaptable production scheduling increased the company's capability to meet
customer demands. The influencing factors on supply chain performance were found to
be inventory management problems, supplier reliability, workforce issues, and
technological adoption, requiring a collaborative approach for long-term supply chain
resilience. The study concluded that a comprehensive approach to technological adoption, workforce development, supplier collaboration, and flexible operations is
fundamental for maximizing performance within the supply chain and building resilience
against future disruptions.
Optimisation of logistics and distribution of parcels in local courier services in South Africa
No full textThis dissertation is submitted in fulfillment of the requirements for the degree of Master of Engineering: Industrial Engineering, Durban University of Technology, Durban, South Africa, 2024.Distribution logistics is a highly integrated supply chain network that generally focuses on the optimal movement of goods and services from consignor to consignee. Given the importance of logistics distribution, courier services suffer a severe problem of experiencing parcel damage which leads to customer complaints and packaging claims. The cardboard packaging for National Logistics Company (NLC) was found to be easily prone damage when in transit and the courier endured consequences such as claim costs that continued to rise every financial year. The aim of the study is to optimise the logistics and distribution of parcels in courier services in terms of cardboard package damages. The data of package damages was drawn from an Enterprise resource planning (ERP) system used at the NLC, together with measurements that were conducted on site. The study adopted a quantitative research approach, and the data was used to reveal the impact of damaged goods to NLC organisation. A fish-bone diagram was developed to represent the potential root-cause of parcels being damaged in the distribution network, and the results revealed that specifications such as packaging size, weight of parcel, internal content packaging utilization, flute corrugated size used for the package and manpower struggling with heavy parcels were potential root-cause of breakages. Furthermore, a value stream map was developed to analyse the operational steps and collect data of the cross-docking performance for a one-month period. Data collection revealed a lower than anticipated throughput capacity, throughput results varied from day-to-day operations which depict low reliability of distributing parcels. Correlation analysis was then used to examine the correlation between packaging weight, size, internal packaging utilization, and flute corrugated size used for a box. The correlation between these variables was ascertained to be moderate. To optimise package size based on weight, dimensions, item and flute size, a regression model was developed to derive the optimal package for items using the Simplex linear programming of the Solver function in Excel. The model revealed that for an item to have an optimal package size, an addition of 2cm must be added to the original size of an item. Furthermore, training solutions were developed to optimize package handling in the logistics and distribution of parcels. The approach for developing training solutions included loading and offloading strategies, methods of staging and sorting cardboard in a vertical flute direction which is also support by the packaging pictorial markings, and the type of equipment to be considered to reduce breakages. The outcome of the research revealed a significant improvement in the overall logistics process and the financial performance of the organisation. Future studies will look at logistics activities of manufacturing cardboard packaging and the development of standard optimal packages which will be derived from supplier product design.
An application of lean six sigma techniques to accelerate the implementation of Kaizen in the film packaging industry
No full textSubmitted in fulfilment of the requirements of Master of Engineering, Durban University of Technology, Durban, South Africa, 2021.The integration of lean six sigma techniques in manufacturing results in substantial improvement and hence a more profitable organization. The case study company is based in South Africa and specialises in manufacturing plastic film, which uses thin micron plastic for food packaging. The main goal of this research was to accelerate the rate of kaizen implementation by utilizing lean six sigma techniques in order to construct a semi-automated model. Lean six sigma is comprised of various problem-solving techniques. In this case study, 5Whys was combined with Ishikawa to construct a semi- automated model for an effective defect trouble shooting closure system. Defect trouble shooting system is also called a “non-conformance closure system”.
It was evaluated that the procedure of non-conformance closure at the company was inadequate; this was identified as a major finding during an external ISO audit. An opportunity to utilize lean techniques was identified and implemented in order to satisfy the objectives of this research. The first objective was to define the requirements of ISO standards in order to find a suitable system that could be used. Defining the requirements was key for the researcher to get an idea of how the model should be constructed to suit ISO standard requirements. The second objective was to evaluate the current method and find the root cause of the problem; this objective highlighted all the possible causes that had resulted in an inadequate procedure for non-conformance closure.
The third objective was to construct a model by integrating lean techniques that matched ISO standards. This objective was implemented in order to satisfy the research goals; a semi-automated model resulted in a catalyst for continual improvement. The fourth objective was to implement the semi-automated model on each non-conformance that was raised and the fifth objective was to reflect by monitoring and recording the results from the semi-automated model. This method resulted in a smooth flow system of non- conformance closure; the major finding closure was accepted after the auditors monitored the new semi-automated method. Automated non-conformance software, which integrates any system that needs corrective action, was recommended, and seven types of waste were recommended for further analysis. This semi-automated model can be used as a future programme parameter for completing an automated system to resolve non-conformances.
Synthesis of a model for optimising a potable water treatment plant and water usage analysis in the Ugu District
No full textSubmitted in fulfilment of the requirements for the degree of Master of Engineering: Industrial Engineering, Durban University of Technology, Durban, South Africa, 2017.Access to clean and adequate water is a universal and basic human right that feeds into the 6th of the 17 Sustainable Development Goals (SDGs). This goal aims at ensuring availability and sustainable management of water and sanitation for all. Clean water is referred to as potable water, which is safe for human consumption and offer low risk of immediate or long term harm. Raw water undergoes rigorous processing which consists of coagulation, sedimentation, filtration, disinfection and storage, to produce potable water. Each module or stage consumes chemicals and energy resources and thus incurs costs.
To achieve the aim of the study, which was to synthesize an optimised potable water treatment network and a water usage analysis model, the Umzinto Water Treatment Plant (UWTP) and its distribution system was used as the study area. This treatment plant is located within Umdoni, a local municipality of the Ugu District Municipality in KwaZulu-Natal Province, South Africa.
This study’s objectives were fourfold and the first objective was to identify and quantify key raw water quality parameters affecting treatment at the UWTP. The second objective was to design a genetic algorithm for the potable water treatment process control. The third objective was to evaluate the Umzinto Water Distribution System’s Non-Revenue Water (NRW) while the fourth objective was to develop a model for water usage analysis.
For the first objective, data for water quality parameters for the water treatment from July 2006 to June 2013 were statistically analysed. This data were collected from the UWTP’s historical records. To improve the data’s integrity it was pre-processed using cubic hermite interpolation. After the pre-processing trend lines and box plots were used to determine the parameters’ significance compared to the standard values stipulated in the South African National Standard (SANS 241). The trend lines were used to analyse the frequency of observations that were higher than the standard values according to SANS 241. The box plots were used to determine the minimum, median, maximum and mean of the data sets. The mean values for each parameter were compared to the SANS 241 value to determine their significance. The raw water quality parameters were then correlated to the chemical dosages for lime, polymer, potassium permanganate and chlorine. The key parameters selected from the correlation analysis were algal count, manganese (Mn), iron (Fe), Escherichia coli, total coliforms, colour, odour, conductivity, turbidity, suspended solids (SS), pH, temperature, total organic carbon (TOC,) and Hardness.
A number of methods can be used to achieve such optimisation, including artificial neural networks, dynamic programming, linear and non-linear programming, and this study utilised a genetic algorithm as an optimisation tool to achieve the second objective of optimising water treatment at the UWTP. For the model development, data from the correlations obtained for objective 1 were used. The model was aimed at reducing the cost of chemical dosage and four chemical dosage prediction models were developed using genetic algorithms and these were then used to produce a combined chemical dosage cost prediction model. The programming interface utilised for these models was Matlab. In developing these models, the data were first pre-processed to remove outliers and fill in the blanks using a Microsoft Excel Add-in that was developed for this particular purpose. The next step involved a curve fitting exercise in Microsoft Excel 2013. Matlab was then used to code the genetic algorithm that combined and optimised the solutions obtained from the curve fittings. The results showed that genetic algorithms can be reliably used to predict the chemical dosages and hence reduce water treatment costs.
After treatment, water is pumped into the distribution system for consumption. It is therefore important to ensure that all the pumped out treated water reaches the consumer. The third objective therefore assessed the NRW for the Umzinto Water Distribution System for the period between July 2013 and June 2014. The data used for this objective was provided by the Ugu District Municipality. The method used combined the top-down approach and the component-based approach. This combined approach was modified to enable the calculation of all the components that are required in a standard South African Water Balance. The results showed that the distribution system had a high value of NRW, which was 27.9% of the System Input Volume. The major component of NRW was Real Losses, that is, losses that can be mitigated by improving maintenance.
The fourth objective was to develop a model for water usage analysis that would reduce the time taken to evaluate NRW and also improve the analysis of the NRW components using Microsoft Visual Basics 2012 and Microsoft SQL Server 2012 development interfaces. The Visual Basics enabled the development of a graphic user interface that was user-friendly and minimised the time taken to learn the software. The software platform developed was able to import the data required to construct a standard International Water Asssociation (IWA) Water Balance, calculate all the components of NRW, store historical data for the water distribution systems and report on a rolling year basis. A model for water usage analysis was developed and made available for usage by practitioners in Ugu District. The model was developed for the specific study area and further studies would be required in order to validate it in a different setting.
The results obtained for the first objective led to the conclusion that, there was very high pollution emanating from communities and activities close to the raw water sources, especially the EJ Smith Dam. The results from the first objective were also used to determine parameters for the models developed in the second objective. From objective two it was concluded that genetic algorithms can be reliably used to predict chemical dosages and hence reduce water treatment costs. The third objective’s results showed that 27.9% of treated water pumped into the distribution system is NRW. Which is a concern because 65% of this are real losses which have maintenance related problems. The fourth objective’s results showed the practicality of designing model that could be used determine all the important components of NRW that would take time to evaluate manually. It would also store historical data for the water distribution system and report on a rolling year basis. Implementation of this software would help minimise the errors associated with manual calculation of NRW and improve the availability of data for research and analysis.
From the research findings, it is recommended that the treatment plant should change the way it is dosing chemicals in the balancing tank. The method currently being used is prone to error. The analysis of NRW showed that Real Losses were a major challenge in the Umzinto Distribution System. There is need to develop a maintenance program to cater for leakage. Communities also need to be educated on the importance of reporting leakage in the network.
Energy assessment and scheduling for energy optimisation of a hot dip galvanising process
No full textSubmitted in fulfilment of the requirements for the Doctorate of Engineering degree in Industrial Engineering, Durban University of Technology, Durban, South Africa, 2021.The dearth of energy sustainability is posing major challenges both locally and glob- ally. Galvanising furnaces are categorised as dominant consumers of electricity in the overall galvanising industry. Relatively little research has been carried out concerning energy optimisation through sequencing or scheduling algorithms by way of enhancing the performance of galvanising lines. In this regard, the research centres on evaluating overall energy performance in this industry. The research sought to introduce an opti- mal energy optimisation-scheduling algorithm for a hot dip galvanising process.
A DMAIC based methodology was presented for the provisioning of a structured prob- lem-solving process for improving energy efficiency in a galvanising process. Its framework embraces an energy sustainability assessment of four batch hot-dip galva- nising plants. Four energy minimisation opportunities were identified and quantifiable energy and cost savings, as well as avoided carbon dioxide emissions were derived from the analysis of one of the plants. Production or zinc used was identified as the main driver for electricity consumption for Plant 1, while the number of dips per month, amount of zinc used, and ambient temperature conditions were identified as the rele- vant variables for developing a regression model for Plant 2. The amount of zinc used and ambient temperature conditions were found to be the relevant variables for Plant 3. The derived regression model for Plant 4 was based on the amount of zinc used and ambient temperature conditions.
The energy performance indicators for a galvanising plant were established through a comparison of actual and expected consumption, energy intensity index, cumulative sum, and specific energy consumption. A bi-objective GECOS algorithm was further introduced to reduce the total energy consumption as well as makespan. The simula- tion results revealed that the GECOS algorithm outperforms McNaughton’s algorithm, Shortest Processing Time Algorithm, and Integer Linear Programming algorithms on minimising makespan on parallel processing machines.
The key contributions to the body of knowledge from the study include a unique eval- uation of electrical energy consumption by a hot-dip galvanising plant, development of an energy consumption baseline and performance indices, and the developed novel bi-objective GECOS algorithm that considers reducing total energy consumption by the process tanks as well as makespan. Future research work may focus on hybrid genetic algorithm-artificial immune system scheduling tools that would derive synergy from the advantages of both algorithms to improve energy performance.
Improvement of a beer packaging line through Pareto analysis, root cause analysis and statistical tracking
No full textIt is imperative for players in the beer industry to increase efficiency continuously to stay ahead of the competition. The prevailing performance of a beer packaging line in terms of engineering stops at the case study plant was below the target set by management, and therefore
improvements were vital. This paper outlines the improvement of a beer packaging line through
Pareto analysis, root cause analysis, and statistical tracking at a beer producer. The procedure commenced with gathering the data for the line and conducting a Pareto analysis on beer loss. It was found that bottle conveyors' downtime was caused by bottle breakages which was also
resulting in beer loss. A root-cause analysis was conducted for high filler fallen bottle stoppages
and possible solutions for process improvement were then formulated and the best solution was implemented. T-Tests were finally deployed as a means of statistical tracking and the results demonstrated a significant process improvement
- …
