Showing 10 results for Wan
Bhagwan Kumar Mishra, Anupam Das,
Volume 32, Issue 4 (IJIEPR 2021)
Abstract
The article highlights the development of a Non-Gaussian Process Monitoring Strategy for a Steel Billet Manufacturing Unit (SBMU). The non-Gaussian monitoring strategy being proposed is based on Modified Independent Component Analysis (ICA) which is a variant of the widely employed conventional ICA. The Independent Components(IC) being extracted by modified ICA technique are ordered as per the variance explained akin to that of Principle Component Analysis (PCA). Whereas in conventional ICA the variance explained by the ICs are not known and thereby causes hindrance in the selection of influential ICs for eventual building of the nominal model for the ensuing monitoring strategy. Hotelling T2 control chart based on modified ICA scores was used for detection of fault(s) whose control limit was estimated via Bootstrap procedure owing to the non-Gaussian distribution of the underlying data. The Diagnosis of the Detected Fault(s) was carried out by employment of Fault Diagnostic Statistic. The Diagnosis of the Fault(s) involved determination of the contribution of the responsible Process and Feedstock characteristics. The non-Gaussian strategy thus devised was able to correctly detect and satisfactory diagnose the detected fault(s)
Mazlan Awang, Mohd Razif Idris, Zuriyati Zakaria,
Volume 33, Issue 3 (IJIEPR 2022)
Abstract
This paper presents an exploratory study on the development of lean readiness index for Malaysian hospitals. A questionnaire survey were obtained from 118 public hospitals and lean readiness model was developed using structural equation modeling (SEM) and the relevant constructs were identified using confirmatory factor analysis. The Lean Readiness Index (LRI) is formulated and a ruler in associate with the LRI were proposed as to meet the objective of the study. The finding to emerge from this study is that only 10.1% of Malaysian public hospitals have ‘good’ readiness status. The study also revealed the overall LRI’s value is 0.617 and, the majority of the hospitals were categorize as having ‘fair’ and ‘weak’ readiness status. The result indicated that training had the strongest association towards lean readiness while communication is the least. This study had revealed the readiness level for lean implementation in Malaysian public hospitals and proposed the required foundation that need to be enhanced before implementing lean.
Nor Mazlina Ghazali, Aqilah Yusoff, Wan Marzuki Wan Jaafar, Salleh Amat, Edris Aden, Azzahrah Anuar,
Volume 34, Issue 2 (IJIEPR 2023)
Abstract
The research aimed to determine the best components of Malaysia-Counsellor Performance Indicator in measuring the counsellor’s performance in Malaysia. This is the first development phase of the M-CPI. This study involved two type of research designs; quantitative and qualitative approach (Mixed Method). The quantitative data has been obtained from 102 respondents and interview with eight (8) counsellors from different settings. Stratified random sampling technique was utilized to select the respondent and proportional stratification was used to determine the sample size of each stratum. A Need Assessment questionnaire has been developed by the researchers as well as the protocol interview. These two instruments were developed based on the literature reviews of previous instruments that have been invented from the western perspective to measure the performance and competency of counsellors. The results of the study were analysed using the descriptive analysis and thematic analysis. Findings have shown that majority counsellors possessed knowledge and skills in conducting counselling session. Most counsellors in the study demonstrated good interpersonal relationship, interaction, multicultural and religiosity and ethics and professionalism. Through this study, to measure the performance of counsellors, the researchers have found that they must equip themselves with knowledge, skill, interpersonal relationship, interaction, multicultural and religiosity and ethics and professionalism aspects. Based on the interview data, there were new components that have been identified to be added in the Malaysia Counsellor Performance Indicator (M-CPI) which include knowledge (theoretical and knowledge transfer), skills (case management, practical skills and academic/professional writing), interpersonal relationship and interaction, cultural and religiosity, professional roles and expertise, ethics and legality, attitudes and personality, referral and articulate philosophy of profession. In future, research should also focus on the validity and reliability of the components listed in the M-CPI.
Muhammad Asrol, Muchammad Arief, Hendra Gunawan,
Volume 34, Issue 3 (IJIEPR 2023)
Abstract
The food industry's supply chain primarily relies on materials that are not environmentally friendly. To address this issue and improve overall performance, the implementation of Green Supply Chain Management (GSCM) becomes crucial. The objective of this research is to analyze the factors influencing the adoption of GSCM and its impact on the performance of the food industry, particularly in Indonesia where there is a high potential for waste production and environmental impact. The study targeted 83 food industry companies as respondents, achieving a response rate of 76.82%. The research employed a Partial Least Squares (PLS) and statistical analysis approach to test hypotheses regarding food industry performance. The findings indicate that GSCM does not directly affect food industry performance. However, GSCM has a positive influence on Green Innovation, which in turn has a positive impact on Company Performance. Green Innovation acts as a mediator between GSCM and Corporate Performance. The implementation of a GSCM at the food industry not only enhances environmental performance but also to improved economic performance. It is emphasized that renewable company innovations should be integrated alongside the adoption of green supply chains. The study highlights that the positive effects of the GSCM are more significant when mediated by green innovation.
Yulin Wan, Md Nor Khalil Bin, Biyuan Lyu, Wei Feng,
Volume 34, Issue 4 (IJIEPR 2023)
Abstract
This study aims to conduct a comprehensive analysis of the existing literature on social presence in order to identify significant research works, contribute valuable insights into emerging research areas, and provide an overview of global research trends. The study also aims to assist future researchers in locating relevant information aligned with their research interests. The research employs bibliometric analysis to examine 1962 journal articles published between 1958 and 2022, focusing on various aspects such as publication outputs, co-authorships among authors and affiliated countries, and co-occurrences of author keywords referenced in the Scopus database. Additionally, the study identifies the most active institutions, productive journals, and prolific authors in the field of social presence. Notably, the analysis reveals a consistent increase in cumulative publication numbers from 2014 to 2018, with an annual increment of 100 articles. More than 55% of the total publications originate from researchers based in China and the United States. Moreover, among the top 15 countries, four of their most prolific universities are ranked among the world's top 100 universities. The findings of the bibliometric study highlight that research on social presence predominantly focuses on captivating themes such as e-learning, social media, computer-mediated communication (CMC), and communities of inquiry (CoI). The primary objective of the study is to identify shifts in publication outputs, co-authorships, affiliated countries, and author keywords, thereby unveiling prevailing publication trends within the field of social presence. The scope of the study primarily centres on the identification of trends through bibliometric analysis. The study's findings indicate an upward trend in the publication of articles concerning social presence, which is expected to continue. Furthermore, co-authorship and co-occurrence investigations are undertaken to assess leading countries and frequently employed keywords in the literature.
Iwa Kustiyawan, Mas Rahman Roestan, Catur Riani,
Volume 34, Issue 4 (IJIEPR 2023)
Abstract
This research aims to identify the initial OEE (Overall Equipment Efficiency) values on automated packaging machines with a 2d barcode track and trace system. Quantitative research methods used to obtain the OEE value, analysis of factors affecting the OEE values, developing a strategy to make improvements, and evaluate these strategies on the level of machine productivity. The importance of the subject lies in the need to improve the efficiency and productivity of pharmaceutical packaging processes. The pharmaceutical industry is facing increasing pressure to optimize operations and reduce waste. Implementing effective performance measurement tools such as Overall Equipment Effectiveness (OEE) can help identify areas for improvement and enhance productivity. This study found that the track-and-trace system was below the company's standard, indicating room for improvement. Then, countermeasures were implemented to increase productivity and machine effectiveness, and the initial OEE value of the automated packaging machine with 2D barcodes improved. Thus, this study demonstrated the effectiveness of the proposed framework in evaluating and improving OEE in pharmaceutical packaging processes, highlighting the significance of digitalization and automation technologies in enhancing productivity.
Halim Dwi Putra, Iphov Kumala Sriwana , Husni Amani ,
Volume 35, Issue 1 (IJIEPR 2024)
Abstract
The construction industry is one of the high-demand industries related to business and projects. Robust materials management that is subject to inventory management is the highest factor to enhance the Supply chain management (SCM) performance that will indicate the project's success within the complexity of the project. This research aims to measure the performance of Supply Chain Management at PT Cahaya Amal Taqwa as a new housing developer who focuses on subsidized housing that faces a project delay because they have less data documentation and analysis from previous projects. The issue is most newcomer construction projects never analyze and measure their supply chain management (SCM) which leads them to confusion about the project improvement. The research uses the Supply Chain Operational Reference (SCOR) method to know how much inventory management impacts supply chain management performance and how it overcomes the issues. Most studies only measure the SCM performance and show which aspects need to be developed without any scheme of solution offered. This research presents the scheme of improvement for the inventory model and provides forecasting for the whole SCM performance after the implementation of a new model of inventory management. The findings confirm that inventory management significantly impacts the whole supply chain management performance in the construction industry. The development of a solution system brought comprehensive results by classifying KPIs for inventory management and an interdependence network was created to define the new model of inventory system for the solution. This research proves that improving an aspect will impact significantly the whole SCM performance instead of improving KPIs one by one.
Dian Dewi, Yustinus Hermanto, Martinus Sianto, Jaka Mulyana, Dian Trihastuti, Ivan Gunawan,
Volume 35, Issue 2 (IJIEPR 2024)
Abstract
Supply chain agility (SCA) has emerged as a significant focus for industries and businesses, serving as a cornerstone for gaining a competitive edge and playing a pivotal role in supply chain management. This importance is further underscored in the context of Product–Service Systems (PSS), which involve the development of both products and services. Despite the existing body of research on SCA and PSS, there has been a notable dearth of empirical studies examining the readiness of PSS SCA. This study makes a substantial contribution by developing a valid and reliable framework to assess the readiness of PSS for supply chain agility. The process involves defining domains, generating items, analyzing agreement among raters, testing for response bias, and conducting exploratory and confirmatory factor analyses. Using structural equation modeling, the model's validity and reliability were evaluated through an online survey with 405 participants from official motorcycle service partners. The findings identify six key capability constructs: collaboration, knowledge transfer, service partner development, information sharing, logistic integration and supply chain agility. This examination of PSS SCA readiness and its constructs provides a validated tool for industry practitioners to enhance their supply chain agility.
Mariam Atwani, Mustapha Hlyal , Jamila El Alami ,
Volume 35, Issue 2 (IJIEPR 2024)
Abstract
In today's dynamic and competitive manufacturing landscape, accurate demand forecasting is paramount for optimizing production processes, reducing inventory costs, and meeting customer demands efficiently. With the advent of Artificial Intelligence (AI), there has been a significant evolution in demand forecasting methods, enabling manufacturers to enhance the accuracy of the forecasts.
This systematic literature review aims to provide a comprehensive overview of the state-of-the-art on demand forecasting models in the manufacturing sector, whether AI-based models or hybrid methods merging both the AI technology and classical demand forecasting methods. The review begins by establishing an overview on demand forecasting methods, it then outlines the systematic methodology used for the literature search.
The review encompasses a wide range of scholarly articles published up to September 2023. A rigorous screening process is applied to select relevant studies. Accordingly, a thorough analysis in the basis of the forecasting methods adopted and data used have been carried out. By synthesizing the existing knowledge, this review contributes to the ongoing advancement of demand forecasting practices in the manufacturing sector providing researchers and practitioners an overview on the advancements on the use of AI models to improve the accuracy of demand forecasting models.
Fakhri Ikhwanul Alifin, Bermawi Priyatna Iskandar, Nadia Fasa, Fransisca Debora,
Volume 35, Issue 2 (IJIEPR 2024)
Abstract
This study develops warranty cost models for repairable products subject to Lemon Laws, encompassing Critical and Non-Critical components forming a multi-component system. Failures can arise naturally or be induced by other components (i.e., failure interaction), defining a lemon if recurrent failures reach a threshold (k) during the warranty period. A lemon declaration triggers a refund or replacement by the manufacturer. Four warranty cost models are proposed from the manufacturer's standpoint, considering failure mechanisms. Increasing failure thresholds in the warranty scheme substantially decreases warranty cost rates. For instance, a threshold (k) of 5 in refund and replacement schemes yields the lowest cost rates of 33.7159 and 25.8249, respectively. Failure interactions escalate total warranty costs; for instance, in a refund scheme (k = 5), costs with failure interaction reach 31.0169 compared to 28.7603 without. Similar trends apply to replacement schemes. Moreover, a lower warranty cost rate will extend the period, indicating regulation fulfillment due to a closer warranty period to the Lemon period. Sensitivity analysis also underscores the role of higher reliability in reducing warranty costs and complying with Lemon Laws. Finally, maintenance strategies and product reliability are emphasized to fulfill Lemon Laws with minimal costs, i.e., fewer warranty claims.
