Adoption Strategy for Electrical and Electronics (E&amp;E) Small and Medium-Sized Enterprises (SMEs): Malaysia IR4.0 Perspective

Balakrishnan, Bavaani a/p; Othman, Zakirah; Zaidi, Mohamad Faizal Ahmad; Yahaya, Wan Ahmad Jaafar Wan

doi:10.37934/araset.28.3.2738

Cited by 2 publications

(2 citation statements)

References 8 publications

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“…This case study could assist decision-makers in developing a robust SPC framework for their organization. The development of framework can help organizations be more resilient in the presence of a technological revolution [53]. Future studies should also benchmark the cognitive skills related to brain-based abilities (i.e., information processing, knowledge acquisition and reasoning) [54] with artificial intuition for automated decision-making methods [55].…”

Section: Discussionmentioning

confidence: 99%

Robust Control Chart Application in Semiconductor Manufacturing Process

Sufinah Dahari,

Muzalwana Abdul Talib,

Adilah Abdul Ghapor

2024

ARASET

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Statistical Process Control (SPC) charts are frequently used in the semiconductor manufacturing environment to monitor process quality and detect special-cause variations, hence, to take corrective actions when necessary. The important aspects of control charts to consider on production floors are identifying the primary objective of implementing control charts, the type of data to monitor and the most appropriate control limits to establish. When the quality data is a type of attribute data like the proportion of defectives from a production lot, a p-chart approach is most suitable. In p-chart applications, although the assumption of normally distributed process data is not mandatory, the widespread practice is to assume the normal distribution of process data when establishing the control limits. Yet again, the reality of industrial settings is that process data are most likely influenced by outliers, resulting in highly skewed distributions. This paper addresses these issues by proposing robust SPC charting techniques to detect special-cause variations in the semiconductor manufacturing processes. Here, we present a case study of a semiconductor company in Malaysia, Dominant Opto Technologies Sdn. Bhd. to propose three robust statistical approaches for monitoring the proportion of defectives in production lots. We apply M-estimates, median, and interquartile range to calculate the upper control limits (UCL) and found that robust estimators are more effective in detecting early process deterioration and capturing the out-of-control (OOC) conditions better than traditional control charts. By proposing robust methods, this study enlightens the practical aspects of process quality improvement for real-life manufacturing setups. Because a high OOC rate may impact manufacturing productivity, we recommend the decision-makers choose the types of control charts based on the implications of each robust approach toward quality and productivity. The significance of this study includes providing insights into setting up the appropriate attribute control charts for detecting defective proportions for professionals and SPC researchers working in these areas.

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Section: Discussionmentioning

confidence: 99%

Robust Control Chart Application in Semiconductor Manufacturing Process

Sufinah Dahari,

Muzalwana Abdul Talib,

Adilah Abdul Ghapor

2024

ARASET

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“…Fachrunnisa et al (2020) correlated SF with strategic sensitivity, leadership cohesion and resource fluidity that enhance technological capabilities. The effects are a higher level of exploration and shifting constraints for the company (Zhou and Wu, 2009). Moreover, the context in which SF should operate needs to be clarified (Ahmadi and Mohd.…”

Section: The Interplay Among Paradoxical Leadershipmentioning

confidence: 99%

The interplay among paradoxical leadership, industry 4.0 technologies, organisational ambidexterity, strategic flexibility and corporate sustainable performance in manufacturing SMEs of Malaysia

Hossain,

Kumar,

Islam

et al. 2023

EBR

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Purpose Manufacturing firms must embrace smart technologies and develop complex leadership approaches to achieve sustainability. Using the dynamic capability theory, this paper aims to examine the influence of the adoption of industry 4.0 technologies (AT) and paradoxical leadership (PL) on corporate sustainable performance (CSP) of manufacturing small-medium enterprises (SMEs) in Malaysia. Moreover, organisational ambidexterity (OA) is a mediator and strategic flexibility (SF) is a moderator in the study. Design/methodology/approach The study is a cross-sectional, quantitative study design that collected 395 usable responses through a simple random sampling technique and a close-ended structured questionnaire. Structural equation modelling (SEM) procedures were followed to analyse the data. Findings The statistical outcome implies that the AT significantly influence CSP and OA and mediate with CSP in the presence of OA. Moreover, PL shows a significant impact on OA, is insignificant on CSP and mediates with OA and CSP. The authors found a significant association between OA and CSP; however, SF did not provide evidence of a moderate effect. Research limitations/implications The findings of this study clarify the role that organisational capabilities (OA, AT, PL and SF) play in fostering sustainability. The authors suggest incorporating SMEs from different geographies in other sectors by applying diverse methodologies and relevant constructs. Practical implications The result injects new perspectives into policy, managerial and individual levels. Installing OA, AT, PL and SF makes SMEs sustainable. Originality/value The empirical validation of the influence of OA and AT on CSP and the interaction of PL and SF enriches the organisational and entrepreneurial literature.

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Adoption Strategy for Electrical and Electronics (E&E) Small and Medium-Sized Enterprises (SMEs): Malaysia IR4.0 Perspective

Cited by 2 publications

References 8 publications

Robust Control Chart Application in Semiconductor Manufacturing Process

Robust Control Chart Application in Semiconductor Manufacturing Process

The interplay among paradoxical leadership, industry 4.0 technologies, organisational ambidexterity, strategic flexibility and corporate sustainable performance in manufacturing SMEs of Malaysia

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