Search results

Purpose – The purpose of this paper is to propose a risk‐based approach for spare parts demand forecast and spare parts inventory management for effective allocation of limited resources. Design/methodology/approach – To meet the availability target and to reduce downtime, process facilities usually maintain inventory of spare parts. The maintaining of non‐optimized spare parts inventory claims more idle investment. Even if it is optimized, lack of attention towards the critical equipment spares could threaten the availability of the plant. This paper deals with the various facets of spare parts inventory management, mainly risk‐based spare parts criticality ranking, forecasting, and effective risk reduction through strategic procurement policy to ensure spare parts availability. A risk‐based approach is presented that helps managing spare parts requirement effectively considering the criticality of the components. It also helps ensuring the adequacy of spare parts inventory on the basis of equipment criticality and dormant failure without compromising the overall availability of the plant. Findings – The paper proposes a risk‐based approach that used conjugate distribution technique with the capability to incorporate historical failure rate as well as expert judgment to estimate the future spare demand through posterior demand distribution. The approach continuously updates the prior distribution with most recent observation to give posterior demand distribution. Hence the approach is unique in its kind. Practical implications – Appropriate spare parts unavailability could have great impact on process operation and result in costly downtime of the plant. Following proposed approach the availability target can be achieved in process industry having limited maintenance resources, by forecasting spare parts demand precisely and maintaining inventory in good condition. Originality/value – Adopting the approach proposed in the paper, risk level can be minimized and plant availability can be maximized within the financial constraint. The resources are allocated to the most critical components and thereby increased availability, and reduce risk.

Studies on remarriages based on census data are not available in Bangladesh. Moreover, questions like why the remarriage rate is declining in Bangladesh despite the increasing trend of divorce rate and what factors are associated with this declining trend of remarriage are not answered yet. Thus the purpose of this study is to assess the prevalence of divorces and the extent to which this has influenced the likelihood of remarriage in Bangladesh.

Univariate, bivariate, and multivariate analyses have been performed by analyzing the most recent and largest sample census data of ever married men and women aged 10 years and above collected in 2011.

The prevalence of remarriage is low in Bangladesh but more common in rural places of residence, substantially larger in slums when compared with non-slums, among Bengali ethnic people, rent-free tenancy, the age group of 45 years and over, the male population, people of Muslim religion, who have no education, and poorest wealth quintile. Muslim religion, slum dwelling status, employed status, media exposure, and urban residence stand out as the major determinants in terms of remarriage. Women having higher education and the richest quintile of households are less likely to be remarried than those who have lower education and are from the poorest wealth quintile background. Males who remarry also followed the same pattern. But remarriage is higher among both the divorced males and females as compared to widowed males and females. Strategic targeting and responsive social policies are needed to be implemented toward the differential pattern of remarriage by sub-groups of the population and their vulnerabilities in relation to their marital status and marital relation, to understand remarriage dynamics in Bangladesh.

The impact of the COVID-19 pandemic provides the scope to conduct online classes in the university teaching methods. This study aims to investigate the impact of technology self-efficacy on students' behavioral intention on the effectiveness of online learning.

This study was conducted with 323 university students using the online survey platform. Data analysis was acquired by implementing the partial least squares technique to obtain the results.

The findings revealed that the COVID-19 pandemic affects technology self-efficacy. Technology self-efficacy has a significance on perceived usefulness (PU) and ease of use, which influences students' behavioral intention to use online learning effectively. The results identified that user innovativeness facilitated the relationship between PU and behavioral intention to use online learning efficiency.

This study has a significant insight into the higher educational institutes and academia that lessons from the impact of the COVID-19 pandemic on technology self-efficacy toward online learning effectiveness.

The imperative to conserve resources and minimize operational expenses has spurred a notable increase in the adoption of lean manufacturing within the context of the circular economy across diverse industries in recent years. However, a notable gap exists in the research landscape, particularly concerning the implementation of lean practices within the pharmaceutical industry to enhance circular economy performance. Addressing this void, this study endeavors to identify and prioritize the pivotal drivers influencing lean manufacturing within the pharmaceutical sector.

The outcome of this rigorous examination highlights that “Continuous Monitoring Process for Sustainable Lean Implementation,” “Management Involvement for Sustainable Implementation” and “Training and Education” emerge as the most consequential drivers. These factors are deemed crucial for augmenting circular economy performance, underscoring the significance of management engagement, training initiatives and a continuous monitoring process in fostering a closed-loop practice within the pharmaceutical industry.

The findings contribute valuable insights for decision-makers aiming to adopt lean practices within a circular economy framework. Specifically, by streamlining the process of developing a robust action plan tailored to the unique needs of the pharmaceutical sector, our study provides actionable guidance for enhancing overall sustainability in the manufacturing processes.

This study represents one of the initial efforts to systematically identify and assess the drivers to LM implementation within the pharmaceutical industry, contributing to the emerging body of knowledge in this area.

This paper aims to report the effect of titanium oxide (TiO₂) particles on the specific wear rate (SWR) of alkaline treated bamboo and flax fiber-reinforced composites (FRCs) under dry sliding condition by using a robust statistical method.

In this research, the epoxy/bamboo and epoxy/flax composites filled with 0–8 Wt.% TiO₂ particles have been fabricated using simple hand layup techniques, and wear testing of the composite was done in accordance with the ASTM G99-05 standard. The Taguchi design of experiments (DOE) was used to conduct a statistical analysis of experimental wear results. An analysis of variance (ANOVA) was conducted to identify significant control factors affecting SWR under dry sliding conditions. Taguchi prediction model is also developed to verify the correlation between the test parameters and performance output.

The research study reveals that TiO₂ filler particles in the epoxy/bamboo and epoxy/flax composite will improve the tribological properties of the developed composites. Statistical analysis of SWR concludes that normal load is the most influencing factor, followed by sliding distance, Wt.% TiO2 filler and sliding velocity. ANOVA concludes that normal load has the maximum effect of 31.92% and 35.77% and Wt.% of TiO2 filler has the effect of 17.33% and 16.98%, respectively, on the SWR of bamboo and flax FRCs. A fairly good agreement between the Taguchi predictive model and experimental results is obtained.

This research paper attempts to include both TiO₂ filler and bamboo/flax fibers to develop a novel hybrid composite material. TiO₂ micro and nanoparticles are promising filler materials, it helps to enhance the mechanical and tribological properties of the epoxy composites. Taguchi DOE and ANOVA used for statistical analysis serve as guidelines for academicians and practitioners on how to best optimize the control variable with particular reference to natural FRCs.