Interventions to Skills Development in the Automotive Manufacturing Sector of South Africa

Competitiveness of the automotive industry is critical to South Africa’s economic sustainability. Recent studies have shown that the automotive sector has consistently contributed over 7% to South Africa’s annual gross domestic product (GDP) and as such, it is particularly imperative to support this sector, through growth-stimulating measures. Economic growth of any nation has long been attributed to the availability of resources, both tangible and intangible. Human capital is thus far the greatest intangible asset recorded in history and it is the key element upon which the success of all sectors is predicated. The availability of foreign direct investment (FDI) has largely been credited to the level of skilled and proficient human resources within an economy. This chapter highlights the strategic position of the South Africa automotive industry, by discussing various skills development interventions recorded within this sector from a domestic standpoint and from an international perspective. It comparatively analyses the approach applied locally with those implemented in other countries, through a historical review of skills development measures within the automotive manufacturing sector. The chapter identifies the major stakeholders, their roles and recognized contributions toward establishing a sustainable automotive sector. The skills development frameworks discussed in this chapter will serve as bases for informed decision to other industries interested in adapting and replicating some of the plausible actions applied in the automotive sector for their own growth

Implementation of lean six sigma for production process optimization in a paper production company

Purpose: This study aims at implementing lean six sigma to evaluate the productivity and manufacturing wastes in the production line of a paper company Methodology/Approach: The study is a case study in nature. The method illustrates how lean six sigma (LSS) is used to evaluate the existing production process in a paper production company with focus on productivity and manufacturing wastes. The study considered a real-time problem of customer’s dissatisfaction. Gathered data were based on machine functionality (up time, down time and cycle time); materials and labour flow at every process stage of the production line. The optimization of the production process was based on lean tools like value stream mapping, process cycle efficiency, Kaizen, 5S and pareto chart Findings: Based on lean six sigma application, it was discovered that the present production performance was below standard and more manufacturing wastes were generated. The present productivity and manufacturing wastes are reported as low process cycle efficiency (23.4 %), low takt time (4.11 sec), high lead time (43200sec), high number of products not conforming to six sigma values, high down time (32.64 %) and excess labour flow (33). After the implementation of the lean six sigma tools for certain periods, there were lots of improvements in the production lines in terms of all the parameters considered. Research Limitations/ Implications: The study has demonstrated application of lean six sigma in the case of solving real-time problems of productivity and manufacturing wastes which have a direct implication on customer’s satisfaction. The lesson learnt and implications presented can still be further modeled using some lean based software for validity Originality/Value: The study has contributed to the body of knowledge in the field of LSS with focus to process-based manufacturing, unlike most literature in the field which concentrated more on discrete based manufacturingPeer Reviewe

Framework assessment for costs of poor quality in higher education processes

Higher education quality costs are escalating daily and the cost of poor quality is becoming excessive. The higher education department has indicated that inefficiencies within the higher education environment are affecting the performance and the return of investments. This research uses 2011 and 2012 records retrieved on Industrial Engineering department from the Management Information System unit of Tshwane University of Technology, Pretoria, South Africa. It focuses on how cost of poor quality can be categorized within higher education environment, and identifies methods which can be used to minimize these costs with the purpose of improving the performance and return of investments. The paper established the cost of poor quality for the department using the teaching input grant, teaching output grant, research output grant, and institutional factor grants, teaching input unit, students' full credit load and among other factors. The results of this research indicated that USD94,3166.24 and USD933,431.92 were lost for the year 2011 and 2012 respectively on just one department and affirmed that failure cost and preventative costs are the main costs associated with higher education inefficiencies and shortfalls. Thus, application of lean enterprise or lean six sigma tools is recommended to salvage the situation

An integrated systems approach to engineering education throughput improvement using Lean Six Sigma

D.Phil. (Engineering Management)Process improvement is essential for an organisation to remain competitive in the global market. Regardless of the type of products or service being rendered, such improvement is essential for remaining profitable and staying at the top of one’s industry market. The Lean Six Sigma (LSS) methodology is a preferred methodology for continuously improving business processes, thereby improving profitability and increasing market share. Higher education institutions are increasingly being placed under pressure to improve throughput and to ensure that that their institutions are sustainable. This focus on higher education inefficiencies has resulted in institutions looking for new ways to improve processes which will lead to increases in throughput. In this study, a LSS framework has been developed and applied for improving engineering education processes..

Improvement of production process variations of bolster spring of a bogie train manufacturing industry: a six-sigma approach

AbstractThe need for improved productivity without sacrificing quality, which is in line the prime target of many manufacturing industries. The aim of this study is to investigate the causes of production variation: a case study of the rail manufacturing industry, South Africa. In this study, the six-sigma Define, Measure, Analyse, Improve and Control (DMAIC) phases were applied to enhance the process capability (long term) in the production of bolster compression springs in the main line of bogie secondary suspension system. In every phase of DMAIC method, a combination of both qualitative and quantitative techniques was utilized. First, process capability index Cpk of the current process was computed which was found less than 1. The results obtained indicated that the process capability index values were found to be 1 after the improvement phase. Hence, significant improvement was achieved in the area of reduction in process variation and product quality after taking corrective actions. From outcomes of the study, it can be concluded that process performance of a train manufacturing plant can be improved significantly by implementing six-sigma DMAIC methodology. The novelty of this study lies in the fact that the implementation of the six-sigma DMAIC phases to enhance the process capability (long term) and minimise variations in the production of bolster compression springs has not be sufficiently highlighted by the existing literature

Research Perspectives in Collaborative Assembly: A Review

In recent years, the emergence of Industry 4.0 technologies has introduced manufacturing disruptions that necessitate the development of accompanying socio-technical solutions. There is growing interest for manufacturing enterprises to embrace the drivers of the Smart Industry paradigm. Among these drivers, human–robot physical co-manipulation of objects has gained significant interest in the literature on assembly operations. Motivated by the requirement for human dyads between the human and the robot counterpart, this study investigates recent literature on the implementation methods of human–robot collaborative assembly scenarios. Using a combination of strings, the researchers performed a systematic review search, sourcing 451 publications from various databases (Science Direct (253), IEEE Xplore (49), Emerald (32), PudMed (21) and SpringerLink (96)). A coding assignment in Eppi-Reviewer helped screen the literature based on ‘exclude’ and ‘include’ criteria. The final number of full-text publications considered in this literature review is 118 peer-reviewed research articles published up until September 2022. The findings anticipate that research publications in the fields of human–robot collaborative assembly will continue to grow. Understanding and modeling the human interaction and behavior in robot co-assembly is crucial to the development of future sustainable smart factories. Machine vision and digital twins modeling begin to emerge as promising interfaces for the evaluation of tasks distribution strategies for mitigating the actual human ergonomic and safety risks in collaborative assembly solutions design