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Resilience as a novel concept has attracted the most attention in the management of engineering systems. The main goal of engineering systems is production assurance and increasing customer satisfaction which depends on the suitable performance of mechanical equipment. “A resilient system is defined as a system that is resistant to disruption and failures and can recover itself and returns to the state before failure as soon as possible in the case of failure.” Estimate the value of the system’s resilience to increase its resilience by covering the weakness in the resilience indexes of the system.

In this article, a suitable approach to estimating resilience in complex engineering systems management in the field of mining has been presented. Accordingly, indexes of reliability, maintainability, supportability, efficiency index of prognostics and health management of the system, and ultimately the organization resilience index, have been used to evaluate the system resilience.

The results of applying this approach indicate the value of 80% resilience if the risk factor is considered and 98% if the mentioned factors are ignored. Also, the value of 58% resilience of this organization’s management group indicates the weakness of situational awareness and weakness in the vulnerable points of the organization.

To evaluate the resilience in this article, five indicators of reliability, maintainability, and supportability are used as performance indicators. Also, organization resilience and the prognostic and health management of the system (PHM) are used as management indicators. To achieve more favorable results, the environmental and operational variables governing the system have been used in performance indicators, and expert experts' opinions have been used in management indicators.

This paper aims to investigate the experimental behavior and the reliability of concrete columns repaired using fiber-reinforced polymers (FRPs) under axial compression loading. The expression of the ultimate axial resistance was assessed from the experimental data of damaged concrete cylinders repaired by externally bonded double-FRP spiral strips.

The tested columns bearing capacity mainly depends of the elasticity modulus of both damaged and undamaged concrete have been considered in addition to the applied load and the cylinder diameter as random variables in the expression of the failure criterion. The reliability indicators were assessed using first order second moment method.

The emphasized test results, statistically fitted show that the strength has been retrofitted for all repaired specimens whatever the degree of initial damage. However, the gain in axial strength is inversely proportional to the degree of damage.

The efficiency of a new FRP repair procedure using double-spiral strips was studied. This research provides a technical and economical solution for retrofitting existing concrete columns. Finally, the random character of the variables that govern the studied system shows the accuracy and safety of the proposed original design.

The article addresses the optimization of safety stock service levels for parts in a repair kit. The work was undertaken to assist a public transit entity that stores thousands of parts used to repair equipment acquired over many decades. Demand is intermittent, procurement lead times are long, and the total inventory investment is significant.

Demand exists for repair kits, and a repair cannot start until all required parts are available. The cost model includes holding cost to carry the part being modeled as well as shortage cost that consists of the holding cost to carry all other repair kit parts for the duration of the part’s lead time. The model combines deterministic and stochastic approaches by assuming a fixed ordering cycle with Poisson demand.

The results show that optimal service levels vary as a function of repair demand rate, part lead time, and cost of the part as a percentage of the total part cost for the repair kit. Optimal service levels are higher for inexpensive parts and lower for expensive parts, although the precise levels are impacted by repair demand and part lead time.

The proposed model can impact society by improving the operational performance and efficiency of public transit systems, by ensuring that home repair technicians will be prepared for repair tasks, and by reducing the environmental impact of electronic waste consistent with the right-to-repair movement.

The optimization model is unique because (1) it quantifies shortage cost as the cost of unnecessary holding other parts in the repair kit during the shortage time, and (2) it determines a unique service level for each part in a repair kit bases on its lead time, its unit cost, and the total cost of all parts in the repair kit. Results will be counter-intuitive for many inventory managers who would assume that more critical parts should have higher service levels.

This research explores mitigating carbon emissions and integrating sustainability in e-commerce logistics by optimizing the multi-depot pollution routing problem with time windows (MDPRPTW). A proposed model contrasts non-collaborative and collaborative decision-making for order assignment among logistics service providers (LSPs), incorporating low-carbon considerations.

The model is substantiated using improved adaptive large neighborhood search (IALNS), tabu search (TS) and oriented ant colony algorithm (OACA) within the context of e-commerce logistics. For model validation, a normal distribution is employed to generate random demand and inputs, derived from the location and requirements files of LSPs.

This research validates the efficacy of e-commerce logistics optimization and IALNS, TS and OACA algorithms, especially when demand follows a normal distribution. It establishes that cooperation among LSPs can substantially reduce carbon emissions and costs, emphasizing the importance of integrating sustainability in e-commerce logistics optimization.

This paper proposes a meta-heuristic algorithm to solve the NP-hard problem. Methodologies such as reinforcement learning can be investigated in future work.

This research can help logistics managers understand the status of sustainable and cost-effective logistics operations and provide a basis for optimal decision-making.

This paper describes the complexity of the MDPRPTW model, which addresses both carbon emissions and cost reduction. Detailed information about the algorithm, methodology and computational studies is investigated. The research problem encompasses various practical aspects related to routing optimization in e-commerce logistics, aiming for sustainable development.

The objective of this paper is to develop a condition-based maintenance (CBM) scheme for pneumatic cylinders. The CBM scheme will detect two common types of air leaking failure modes and identify the leaky/faulty cylinder. The successful implementation of the proposed scheme will reduce energy consumption, scrap and rework, and time to repair.

Effective implementation of maintenance is important to reduce operation cost, improve productivity and enhance quality performance at the same time. Condition-based monitoring is an effective maintenance scheme where maintenance is triggered based on the condition of the equipment monitored either real time or at certain intervals. Pneumatic air systems are commonly used in many industries for packaging, sorting and powering air tools among others. A common failure mode of pneumatic cylinders is air leaks which is difficult to detect for complex systems with many connections. The proposed method consists of monitoring the stroke speed profile of the piston inside the pneumatic cylinder using hall effect sensors. Statistical features are extracted from the speed profiles and used to develop a fault detection machine learning model. The proposed method is demonstrated using a real-life case of tea packaging machines.

Based on the limited data collected, the ensemble machine learning algorithm resulted in 88.4% accuracy. The algorithm can detect failures as soon as they occur based on majority vote rule of three machine learning models.

Early air leak detection will improve quality of packaged tea bags and provide annual savings due to time to repair and energy waste reduction. The average annual estimated savings due to the implementation of the new CBM method is $229,200 with a payback period of less than two years.

To the best of the authors’ knowledge, this paper is the first in terms of proposing a CBM for pneumatic systems air leaks using piston speed. Majority, if not all, current detection methods rely on expensive equipment such as infrared or ultrasonic sensors. This paper also contributes to the research gap of economic justification of using CBM.

The study analyzes the relationship between homeownership and financial investment of households in the context of emerging markets like India. It also examines how homeownership affects the portfolio decisions of Indian households.

Using the nationally representative All-India Debt and Investment Survey of 2019 and employing an instrumental variable approach, the authors analyze the relationship between homeownership and the share of financial assets held by Indian households. The study also employs several sensitivity checks, including alternate estimation techniques and alternative definitions of the housing variables, and accounts for additional factors to ensure that the authors are able to capture the effect of homeownership on the outcome variable.

The analysis suggests homeownership crowds out financial investment in India due to high repair and maintenance costs. The negative effect is mainly observed in urban households. Further, the findings imply that homeownership leads households to reallocate their asset portfolio. Homeowners have a lower share in liquid short term deposits, indicating the high liquidity risk of their portfolios. On the other hand, homeownership increases the share of long term retirement funds along with no effect on risky asset share. The authors observe that the crowding out effect is more striking for younger households and poorer households with low income, and the effect is lower for indebted households.

The findings underscore the need for financial awareness programs so that housing does not crowd out liquid investments of households. Additionally, the results highlight that policies should first focus on young and poor households as the negative effect is more prominent for these groups. Finally, there is scope for policies to support repair and maintenance costs incurred by vulnerable households to reduce the negative effect of housing on liquid financial investments.

This paper is among the few studies that provide insights into how homeownership relates to financial investment and portfolio decisions in the context of an emerging economy. Furthermore, the heterogeneous effects based on poor economic status and age underscore the need for complementary policies.

Even though it is widely used, reinforced concrete (RC) is susceptible to damage from various environmental factors. The hazard of a fire attack is particularly severe because it may cause the whole structure to collapse. Furthermore, repairing and strengthening existing structures with high-performance concrete (HPC) has become essential from both technical and financial points of view. In particular, studying the postfire behavior of HPC with normal strength concrete substrate requires experimental and numerical investigations. Accordingly, this study aims to numerically investigate the post-fire behavior of reinforced composite RC slabs.

Consequently, in this study, a numerical analysis was carried out to ascertain the flexural behavior of simply supported RC slabs strengthened with HPC and exposed to a particularly high temperature of 600°C for 2 h. This behavior was investigated and analyzed in the presence of a number of parameters, such as HPC types (fiber-reinforced, 0.5% steel, polypropylene fibers [PPF], hybrid fibers), strengthening side (tension or compression), strengthening layer thickness, slab thickness, boundary conditions, reinforcement ratio and yield strength of reinforcement.

The results showed that traction-separation and full-bond models can achieve accuracy compared with experimental results. Also, the fiber type significantly affects the postfire performance of RC slab strengthened with HPC, where the inclusion of hybrid fiber recorded the highest ultimate load. While adding PPF to HPC showed a rapid decrease in the load-deflection curve after reaching the ultimate load.

The proposed model accurately predicted the thermomechanical behavior of RC slabs strengthened with HPC after being exposed to the fire regarding load-deflection response, crack pattern and failure mode. Moreover, the considered independent parametric variables significantly affect the composite slabs’ behavior.

This study aims on a broad review of Concrete's Rheological Properties. The Concrete is a commonly used engineering material because of its exquisite mechanical interpretation, but the addition of constituent amounts has significant effects on the concrete’s fresh properties. The workability of the concrete mixture is a short-term property, but it is anticipated to affect the concrete’s long-term property.

In this review, the concrete and workability definition; concrete’s rheology models like Bingham model, thixotropy model, H-B model and modified Bingham model; obtained rheological parameters of concrete; the effect of constituent’s rheological properties, which includes cement and aggregates; and the concrete’s rheological properties such as consistency, mobility, compatibility, workability and stability were studied in detail.

Also, this review study has detailed the constituents and concrete’s rheological properties effects. Moreover, it exhibits the relationship between yield stress and plastic viscosity in concrete’s rheological behavior. Hence, several methods have been reviewed, and performance has been noted. In that, the abrasion resistance concrete has attained the maximum compressive strength of 73.6 Mpa; the thixotropy approach has gained the lowest plastic viscosity at 22 Pa.s; and the model coaxial cylinder has recorded the lowest stress rate at 8 Pa.

This paper especially describes the possible strategies to constrain improper prediction of concrete’s rheological properties that make the workability and rheological behavior prediction simpler and more accurate. From this, future guidelines can afford for prediction of concrete rheological behavior by implementing novel enhancing numerical techniques and exploring the finest process to evaluate the workability.

The purpose of this study is to investigate the impact of greening and promotional effort dependent stochastic market demand on the remanufacturer's and the collector's profits when the quality of used products for remanufacturing is uncertain in a reverse supply chain.

The proposed model is developed to obtain optimal profits for the remanufacturer, the collector and the whole supply chain. Both the centralized and decentralized scenarios are considered. To motivate the collector through profit enhancement, the remanufacturer designs a cost-sharing contract. Through numerical examples and sensitivity analysis, the consequences of greenness and promotional effort on optimal profits are investigated.

The results show that the remanufacturer gets benefited from greening and promotional effort enhancement. However, a higher value of minimum acceptable quality level decreases the profits of the manufacturer and the collector. A cost-sharing contract coordinates the supply chain and improves the remanufacturer's and the collector's profits. Besides green innovation, remanufacturing mitigates the harmful effects of waste in the environment.

Two different viewpoints of remanufacturing are considered here – environmental sustainability and economic sustainability. This paper considers a reverse supply chain with a remanufacturer who remanufactures the used products collected by the collector. The quality of used products is uncertain, and customer demand is stochastic, green and promotional effort sensitive. These two types of uncertainty with green and promotional effort sensitive customer demand differs the current paper from the existing literature.

Although some architects have found spatial order and proportion strategy effective in designing the environment for autistic children, it is not clear what spatial ratios are preferred for autistic people. Therefore, this study aims to find the desired ratio among autistic and non-autistic children.

The scale model questionnaire was chosen to determine the difference in the ratio preferences for autistic and non-autistic children, whereas two access types between the space zones are also considered. The questionnaire was administered to 50 autistic children, with a half-and-half distribution of moderate and mild autism groups, while males are twofold. It was also administered to 50 non-autistic children, approximately equal in terms of gender division. The scale model was designed in the form of a dollhouse to be played with a doll in 6 varied rooms categorized by 3 different ratios (1:1, golden ratio, 1.6:1 and 5:2) and 2 access types (linear and radial access) to measure how many times each room was selected by each group to run numerical analysis.

It was shown that, although the golden ratio has been previously considered in space design for autistic children, they appealed to the ratio of 2:5 with high frequency. While there is a significant difference between the spatial ratios preferred by autistic and non-autistic children choosing the golden ratio, the same type of space access system is preferred by both groups in their results.

Despite the prevalent use of the golden ratio in design for autism design, this research shaped an empirical study for autistic users concluding a different perspective in design for autism.