25 research outputs found
Modelling and simulation for the joint maintenance-inventory optimisation of production systems
Simulation methodologies are developed to model the joint optimization of preventive maintenance and spare parts inventory for a specific industrial plant under different production configurations. First, spare parts provisioning for a single-line system is considered, with the assumption that the demand is driven by maintenance requirements. The results indicate that a periodic review policy with replenishment as frequent as inspection is cost-optimal. Second, the joint optimization model for a multi-line (parallel) system is developed. It is found that a just-in-time review policy with inspection as frequent as replenishment produces the lowest cost policy. In this latter case, an implication of the proposed methodology is that, where mathematical modelling is intractable, or the use of certain assumptions make them impractical, simulation modelling is an appropriate solution tool. Under both production settings, the long-run average cost per unit time is used as the optimality criterion for the comparison of several policies
Joint optimisation of inspection maintenance and spare parts provisioning: a comparative study of inventory policies using simulation and survey data
The demand for industrial plant spare parts is driven, at least in part, by maintenance requirements. It is therefore important to jointly optimise planned maintenance and the associated spare parts inventory using the most appropriate maintenance and replenishment policies. In this simulation-based study, we address this challenge in the context of the random failure of parts in service and the replacement of defective parts at inspections of period T. Inspections are modelled using the delay-time concept. A number of simultaneous periodic review and continuous review replenishment policies are compared. A paper making plant provides a real context for the presentation of our ideas. We survey practitioners working with such plant to collect real data that inform the values of parameters in the models. Our simulation results indicate that a periodic review policy with ordering that is twice as frequent as inspection is cost optimal in the context of the plant that we study. For the purpose of comparison, we also present and discuss the characteristics of the various policies considered
Optimisation of inspection policy for multi-line production systems
This paper develops a simulation model to determine the cost-optimum inspection policy for a multi-line production system taking account of simultaneous downtime. The machines in the multi-line system are subject to a two stage failure process that is modelled using the delay-time concept. Our study indicates that: consecutive inspection of lines with priority for failure repair is cost-optimal, with a cost reduction of 61% compared to a ‘run-to-failure’ policy; and maintainers need to be responsive to operational requirements. Our ideas are developed in the context of a case study of a plant with three parallel lines, one of which is on cold-standby.
Keywords: maintenance; delay-time model; simulation; production; parallel lines; manufacturing; preventive maintenance
Modelling and simulation for the joint optimisation of inspection maintenance and spare parts inventory in multi-line production settings
A simulation methodology is developed to model the joint optimisation of preventive maintenance and spare parts inventory in multi-line settings. The multi-line machines are subject to failure, based on the delay-time concept, and a selection of policies are used for the replenishment of the machines’ critical component. Production lines of varied configurations are modelled and described in three principal chapters. Firstly, the optimisation of preventive maintenance for a multi-line production system is developed in the context of a case study. The policy proposed indicates that consecutive inspection with priority for failure repair is cost-optimal, which suggests a substantial maintenance cost reduction of 61% compared to the run-to-failure policy. The contribution of this study is first and foremost in narrowing the gap between the theory and practice of managing multi-line systems, and in particular, that the scenarios and policies considered have important economic and engineering implications. In a second study, spare parts provisioning for a single-line system is considered, given that the demand for industrial plant spare parts should be driven, at least in part, by maintenance requirements. A paper-making plant provides a real context, for which simulation models are developed to jointly optimise the planned maintenance and the associated spare part inventory. This challenge is addressed in the context of the failure of parts in service and the replacement of defective parts at inspections of period T, using the delay-time concept, and a selection of replenishment policies. The results indicate that a periodic review policy with replenishment twice as frequent as inspection is cost-optimal. Further discussions and sensitivity analysis give insights into the characteristics and features of the policies considered. Finally, in the third study, the joint optimisation of preventive maintenance and the associated spare parts inventory for a multi-line system is developed using an idealised context. It is found that a review policy with inspection as frequent as replenishment using just-in-time (JIT) ordering is cost-optimal, and also the lowest risk policy; it is associated with the lowest simultaneous machine downtime and low stock-out cost-rates. This is a significant contribution to the literature. An implication of the proposed methodology is that, where mathematical modelling is intractable, or the use of certain assumptions make them less practical, simulation modelling is an appropriate solution tool. Throughout this thesis, the long-run average cost per unit time or cost-rate is used as the optimality criterion. In other contexts, one may wish to use availability or reliability instead. To do so would not change the methodology that is presented here
Link between single nucleotide polymorphism of rs266729 and rs2241766 in the ADIPOQ gene and gestational diabetes in an Iranian population
Background: The manuscript investigates the association between adiponectin gene (ADIPOQ) polymorphisms and gestational diabetes mellitus (GDM) in an Iranian population. Methods: We designed a case-control study involving 265 normal glucose tolerant (NGT) women and 297 GDM patients. Three adiponectin single-nucleotide polymorphisms (rs1501299, rs266729 and rs2241766) were genotyped by polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP), and the protein level was measured by the enzyme-linked immunosorbent assay. Other biochemical parameters were assessed by conventional laboratory methods. Results: We found that rs266729 and rs2241766 were significantly associated with GDM. The genotypes analysis indicated that for rs266729, 51(61.4) of the 83 GDM patients had GG genotype, and 32(38.6) GC/CC genotype and for rs2241766, 75(58.6) of the 128 GDM patients had TT genotype, and 53(41.4) GG/GT genotype. The relation between other single-nucleotide polymorphisms (rs1501299) and GDM was not observed. Conclusion: The ADIPOQ genetic polymorphisms were associated with GDM in our studied population. © 201
Fit between humanitarian professionals and project requirements: hybrid group decision procedure to reduce uncertainty in decision-making
Choosing the right professional that has to meet indeterminate requirements is a critical aspect in humanitarian development and implementation projects. This paper proposes a hybrid evaluation methodology for some non-governmental organizations enabling them to select the most competent expert who can properly and adequately develop and implement humanitarian projects. This methodology accommodates various stakeholders’ perspectives in satisfying the unique requirements of humanitarian projects that are capable of handling a range of uncertain issues from both stakeholders and project requirements. The criteria weights are calculated using a two-step multi-criteria decision-making method: (1) Fuzzy Analytical Hierarchy Process for the evaluation of the decision maker weights coupled with (2) Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) to rank the alternatives which provide the ability to take into account both quantitative and qualitative evaluations. Sensitivity analysis have been developed and discussed by means of a real case of expert selection problem for a non-profit organisation. The results show that the approach allows a decrease in the uncertainty associated with decision-making, which proves that the approach provides robust solutions in terms of sensitivity analysis
Recommended from our members
Global age-sex-specific mortality, life expectancy, and population estimates in 204 countries and territories and 811 subnational locations, 1950–2021, and the impact of the COVID-19 pandemic: a comprehensive demographic analysis for the Global Burden of Disease Study 2021
Background
Estimates of demographic metrics are crucial to assess levels and trends of population health outcomes. The profound impact of the COVID-19 pandemic on populations worldwide has underscored the need for timely estimates to understand this unprecedented event within the context of long-term population health trends. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 provides new demographic estimates for 204 countries and territories and 811 additional subnational locations from 1950 to 2021, with a particular emphasis on changes in mortality and life expectancy that occurred during the 2020–21 COVID-19 pandemic period.
Methods
22 223 data sources from vital registration, sample registration, surveys, censuses, and other sources were used to estimate mortality, with a subset of these sources used exclusively to estimate excess mortality due to the COVID-19 pandemic. 2026 data sources were used for population estimation. Additional sources were used to estimate migration; the effects of the HIV epidemic; and demographic discontinuities due to conflicts, famines, natural disasters, and pandemics, which are used as inputs for estimating mortality and population. Spatiotemporal Gaussian process regression (ST-GPR) was used to generate under-5 mortality rates, which synthesised 30 763 location-years of vital registration and sample registration data, 1365 surveys and censuses, and 80 other sources. ST-GPR was also used to estimate adult mortality (between ages 15 and 59 years) based on information from 31 642 location-years of vital registration and sample registration data, 355 surveys and censuses, and 24 other sources. Estimates of child and adult mortality rates were then used to generate life tables with a relational model life table system. For countries with large HIV epidemics, life tables were adjusted using independent estimates of HIV-specific mortality generated via an epidemiological analysis of HIV prevalence surveys, antenatal clinic serosurveillance, and other data sources. Excess mortality due to the COVID-19 pandemic in 2020 and 2021 was determined by subtracting observed all-cause mortality (adjusted for late registration and mortality anomalies) from the mortality expected in the absence of the pandemic. Expected mortality was calculated based on historical trends using an ensemble of models. In location-years where all-cause mortality data were unavailable, we estimated excess mortality rates using a regression model with covariates pertaining to the pandemic. Population size was computed using a Bayesian hierarchical cohort component model. Life expectancy was calculated using age-specific mortality rates and standard demographic methods. Uncertainty intervals (UIs) were calculated for every metric using the 25th and 975th ordered values from a 1000-draw posterior distribution.
Findings
Global all-cause mortality followed two distinct patterns over the study period: age-standardised mortality rates declined between 1950 and 2019 (a 62·8% [95% UI 60·5–65·1] decline), and increased during the COVID-19 pandemic period (2020–21; 5·1% [0·9–9·6] increase). In contrast with the overall reverse in mortality trends during the pandemic period, child mortality continued to decline, with 4·66 million (3·98–5·50) global deaths in children younger than 5 years in 2021 compared with 5·21 million (4·50–6·01) in 2019. An estimated 131 million (126–137) people died globally from all causes in 2020 and 2021 combined, of which 15·9 million (14·7–17·2) were due to the COVID-19 pandemic (measured by excess mortality, which includes deaths directly due to SARS-CoV-2 infection and those indirectly due to other social, economic, or behavioural changes associated with the pandemic). Excess mortality rates exceeded 150 deaths per 100 000 population during at least one year of the pandemic in 80 countries and territories, whereas 20 nations had a negative excess mortality rate in 2020 or 2021, indicating that all-cause mortality in these countries was lower during the pandemic than expected based on historical trends. Between 1950 and 2021, global life expectancy at birth increased by 22·7 years (20·8–24·8), from 49·0 years (46·7–51·3) to 71·7 years (70·9–72·5). Global life expectancy at birth declined by 1·6 years (1·0–2·2) between 2019 and 2021, reversing historical trends. An increase in life expectancy was only observed in 32 (15·7%) of 204 countries and territories between 2019 and 2021. The global population reached 7·89 billion (7·67–8·13) people in 2021, by which time 56 of 204 countries and territories had peaked and subsequently populations have declined. The largest proportion of population growth between 2020 and 2021 was in sub-Saharan Africa (39·5% [28·4–52·7]) and south Asia (26·3% [9·0–44·7]). From 2000 to 2021, the ratio of the population aged 65 years and older to the population aged younger than 15 years increased in 188 (92·2%) of 204 nations.
Interpretation
Global adult mortality rates markedly increased during the COVID-19 pandemic in 2020 and 2021, reversing past decreasing trends, while child mortality rates continued to decline, albeit more slowly than in earlier years. Although COVID-19 had a substantial impact on many demographic indicators during the first 2 years of the pandemic, overall global health progress over the 72 years evaluated has been profound, with considerable improvements in mortality and life expectancy. Additionally, we observed a deceleration of global population growth since 2017, despite steady or increasing growth in lower-income countries, combined with a continued global shift of population age structures towards older ages. These demographic changes will likely present future challenges to health systems, economies, and societies. The comprehensive demographic estimates reported here will enable researchers, policy makers, health practitioners, and other key stakeholders to better understand and address the profound changes that have occurred in the global health landscape following the first 2 years of the COVID-19 pandemic, and longer-term trends beyond the pandemic
Serum selenium level in patients with gastric non-cardia cancer and functional dyspepsia
BACKGROUND:
Gastric cancer (GC) is the most common gastrointestinal cancer in Iran. Helicobacter pylori (H. pylori) accounts as one of the main risk factors for gastric non-cardia cancer (GNCC). It is suggested that high serum selenium level may have a protective role in GNCC. In this cross-sectional study, we determined the serum Se level and the status of H. pylori infection in two populations with GC and functional dyspepsia (FD).
METHODS:
The enrolled patients were 85 (27 women, 58 men) with recent pathologically proven GNCC (adenocarcinoma) and 85 (34 women, 51 men) FD patients. Serum Se was measured by atomic absorption spectrophotometry. H. pylori IgG antibody was detected by quantitative enzyme immunoassay.
RESULTS:
The mean age in the GNCC and FD patients were 62.85±14.6 and 58.9±14.7 years, respectively (P=0.08). The serum selenium levels were 111.6±27.7 and 129.9±32.1 μg/L (mean±SD) in GNCC and FD patients, respectively (P<0.001). The frequency of H. pylori infection was 49.4% (n=42) and 68.2% (n=58) in GNCC and FD patients (P=0.013). The crude and adjusted odds ratio (OR) between GNCC and the linear effect of serum selenium level were 0.98 and 0.982, respectively (P=0.002). This means that each unit increase in serum selenium level decreases the odds of cancer by 2%.
CONCLUSION:
Serum selenium level was significantly lower in GNCC cases. It suggests that lower serum selenium might have some association with the risk of GNCC. H. pylori infection does not play a significant impact on this association