Indra Gunawan

Prof. Indra Gunawan

The University of Adelaide, Adelaide, South Australia
orcid

Research Focus & Metrics

Academic Career Length

11Years (2016-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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26 June 2020 in Systems Research and Behavioral Science
Verified
Journal Article
Closed access
PDF file
CHChristian Hoyer
Christian Hoyer
IGIndra Gunawan
Indra Gunawan
CRCarmen Haule Reaiche
Carmen Haule Reaiche

1 November 2024 in Journal of Construction Engineering and Management
Verified
Journal Article
Closed access
NWNavodi Wijayarathne
Navodi Wijayarathne
IGIndra Gunawan
Indra Gunawan
FSFrank Schultmann
Frank Schultmann

21 June 2018 in Systems Research and Behavioral Science
Verified
Journal Article
Closed access
PDF file
SZSeyed Ashkan Zarghami
Seyed Ashkan Zarghami
IGIndra Gunawan
Indra Gunawan
FSFrank Schultmann
Frank Schultmann

30 October 2022 in Safety Science
Verified
Journal Article
Closed access
BLBenjamin Luther
Benjamin Luther
IGIndra Gunawan
Indra Gunawan
NNNam Nguyen
Nam Nguyen

26 October 2018 in International Journal of Lean Six Sigma
Verified
Journal Article
Closed access
ASAgung Sutrisno
Agung Sutrisno
IGIndra Gunawan
Indra Gunawan
IVIwan Vanany
Iwan Vanany
MAMohammad Asjad
Mohammad Asjad
Wahyu CaesarendraWahyu Caesarendra
Wahyu Caesarendra
Purpose: Proposing an improved model for evaluating criticality of non-value added (waste) in operation is necessary for realizing sustainable manufacturing practices. The purpose of this paper is concerning on improvement of the decision support model for evaluating risk criticality lean waste occurrence by considering the weight of modified FMEA indices and the influence of waste-worsening factors causing the escalation of waste risk magnitude. Design/methodology/approach: Integration of entropy and Taguchi loss function into decision support model of modified FMEA is presented to rectify the limitation of previous risk reprioritization models in modified FMEA studies. The weight of the probability components and loss components are quantified using entropy. A case study from industry is used to test the applicability of the integration model in practical situation. Findings: The proposed model enables to overcome the limitations of using subjective determination on the weight of modified FMEA indices. The inclusion of the waste-worsening factors and Taguchi loss functions enables the FMEA team to articulate the severity level of waste consequences appropriately over the use of ordinal scale in ranking the risk of lean waste in modified FMEA references. Research limitations/implications: When appraising the risk of lean waste criticality, ignorance on weighting of FMEA indices may be inappropriate for an accurate risk-based decision-making. This paper provides insights to scholars and practitioners and others concerned with the lean operation to understand the significance of considering the impact of FMEA indices and waste-worsening factors in evaluating criticality of lean waste risks. Practical implications: The method adopted is for quantifying the criticality of lean waste and inclusion of weighting of FMEA indices in modified FMEA provides insight and exemplar on tackling the risk of lean waste and determining the most critical waste affecting performability of company operations. Originality/value: Integration of the entropy and Taguchi loss function for appraising the criticality of lean waste in modified FMEA is the first in the lean management discipline. These findings will be highly useful for professionals wishing to implement the lean waste reduction strategy.

2 May 2017 in International Journal of Quality & Reliability Management
Verified
Journal Article
Closed access
IGIndra Gunawan
Indra Gunawan
FSFrank Schultmann
Frank Schultmann
SZSeyed Ashkan Zarghami
Seyed Ashkan Zarghami
Purpose: The purpose of this paper is to review the different interpretations of four key performance indicators of water distribution networks (WDNs): reliability, resilience, redundancy and robustness. It then addresses a range of metrics which have been developed to assess the performance of critical infrastructures, in particular WDNs. Design/methodology/approach: The paper provides a comprehensive review and categorization of performance indicators of WDNs. The main focus is on papers addressing performance indicators of water distribution systems, additionally papers on application of complex system approach to critical infrastructures are also included. Findings: Due to this complexity, a wide range of interpretation of WDNs performance indicators exists in the literature. This represents a significant impediment toward universally accepted interpretation of these indicators Accurate assessment of WDNs’ performance depends on clear definition of system performance indicators as well as accurate quantifying of these indicators. The application of 18 metrics as a basis for assessing the system performance have been reviewed in this paper and none are particularly significant as standalone values. Combination of these indicators are required to accurately indicate the performance of WDNs. Originality/value: The authors believe that this paper can be a valuable source of information for academic researchers and practitioners and suggests a roadmap for future works.