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The purpose of this paper is to facilitate green supply chain (GSC) managers and planners to model and access GSC risks and probable failures. This paper proposes to use the fuzzy failure mode and effects analysis (FMEA) approach for assessing the risks associated with GSC for benchmarking the performance in terms of effective GSC management adoption and sustainable production.

Initially, different failure modes are defined using FMEA analysis, and in order to decide the risk priority, the risk priority number (RPN) is determined. Such priority numbers are typically acquired from the judgment decisions of experts that could contain the element of vagueness and imperfection due to human biases, and it may lead to inaccuracy in the process of risk assessment in GSC. In this study, fuzzy logic is applied to conventional FMEA to overcome the issues in assigning RPNs. A plastic manufacturer GSC case exemplar of the proposed model is illustrated to present the authenticity of this method of risk assessment.

Results indicate that the failure modes, given as improper green operating procedure, i.e. process, operations, etc. (R6), and green issues while closing the loop of GSC (R14) hold the highest RPN and FRPN scores in classical as well as fuzzy FMEA analysis.

The present research work attempts to propose an evaluation framework for risk assessment in GSC. This paper explores both sustainable developments and risks related to efficient management of GSC initiatives in a plastic industry supply chain context. From a managerial perspective, suggestions are also provided with respect to each failure mode.

Product portfolio management is a strategic concern. Product portfolio management includes decisions associated with adding new products, maintaining existing products and deleting or phasing out problematic products. This paper first introduces a framework to identify risks of product deletion along supply chain activities. It utilizes failure mode and effects analysis (FMEA) to identify, analyse and evaluate product deletion risks on supply chains and proposes managerial implications for risk management in dynamic business scenarios. It is meant to build upon and address a gap in the product deletion and supply chain linkage literature.

FMEA is utilized in this study to structure and manage potential risks in product deletion decision-making on supply chains. FMEA is based on an analysis of severity, occurrence and detectability of failure modes. FMEA provides methods to help identify managerial preventive solutions to avoid and mitigate risk consequences of such decisions.

Ten top product deletion risks are identified in this study; discussions of their negative impact on supply chain performance, and possible managerial recommendations are followed for risk control, monitor and elimination.

Findings help managers to predict, avoid and mitigate risk consequences of product deletion decisions; especially those related to the supply chain. A framework to structure various risks of product deletion in the supply chain can be useful to both practitioners and researchers.

This study advances product portfolio management through enhanced understanding of product deletion decision-making in organizations; and especially contributes to a broader investigation of such decisions in supply chain management. It also structures the factors that play a role in identifying risks.

FEW engineering products receive the abuse to which aero engines are subjected in wartime and few mechanical devices are produced in which the margin of safety and failure is so small and yet so vital. Failures on a large scale are, therefore, inevitable and their consideration in detail would present a task of prohibitive magnitude but what little is known with any completeness and certainty can offer some useful data. Consideration of a large number of different makes of engines overhauled during wartime has revealed an amazing complexity of facts; it has shown that failures have developed from almost every conceivable cause which, in turn, have produced every conceivable result. There are few tangible pronouncements which can be made on the subject but nevertheless distinct common tendency has been observed which is sufficiently consistent to be worth consideration. This concerns the general trend of failures and will be referred to later; but with regard to failures in detail, the only safe statement to make is that invariably different parts‐fail on different types of engines subjected to similar conditions of severity in operation. The reason for this is not hard to find, and complexity of design in modern aero engines prohibits the mechanical ideal of simultaneous failure of adjacent parts subjected to a given overload. Not only is the exact functional strength of each individual part hardly known but the loadings which it has to endure cannot be foreseen.

This paper aims to determine the effect of exposure of underground electrical cables to chemically contaminated water.

Visual inspection and photography were carried out to record the appearance of electrical cables. Failed and un-failed cable samples were collected and analyzed using light microscopy, scanning electron microscopy coupled with energy-dispersive X-ray spectroscopy and Fourier transform infrared spectroscopy. Sand and water samples were chemically tested for contaminants.

Underground low-voltage 0.6/1-kV cross-linked polyethene insulated cables belonging to a chemical production plant suffered failure after four years of service. Excavation of the cable trench revealed that the cables were buried in sand polluted with chemically contaminated water. The cables were discolored and covered with corrosion deposits. Experimental results indicated that the cable insulation was heavily degraded and the outer jacket of polyvinyl chloride exhibited cracks that had penetrated through its thickness. Water and sand surrounding the cable were found to have high concentrations of ammonia. Mechanical testing of the cables indicated high values of stiffness that could contribute to the formation of cracks at the surface.

It was concluded that contamination in the water had degraded the cable, resulting in the development of a network of branched cracks within the cable insulation through which water could permeate, leading to eventual failure of the cable. Accelerated degradation took place due to exposure to the contaminated environment, which promoted aging and brittleness. Continued exposure of electric cables to contamination would lead to power failures and plant shutdowns.

This paper provides an account of a failure investigation of low-voltage electrical cable buried underground. It discusses the role of contaminated environment in the eventual failure of electrical cable due to corrosion. This information will be useful for plant engineers and project managers working in any industry that makes use of chemicals.

Assessing the failure probability of engineering structures is still a challenging task in the presence of various uncertainties due to the involvement of expensive-to-evaluate computational models. The traditional simulation-based approaches require tremendous computational effort, especially when the failure probability is small. Thus, the use of more efficient surrogate modeling techniques to emulate the true performance function has gained increasingly more attention and application in recent years. In this paper, an active learning method based on a Kriging model is proposed to estimate the failure probability with high efficiency and accuracy.

To effectively identify informative samples for the enrichment of the design of experiments, a set of new learning functions is proposed. These learning functions are successfully incorporated into a sampling scheme, where the candidate samples for the enrichment are uniformly distributed in the n-dimensional hypersphere with an iteratively updated radius. To further improve the computational efficiency, a parallelization strategy that enables the proposed algorithm to select multiple sample points in each iteration is presented by introducing the K-means clustering algorithm. Hence, the proposed method is referred to as the adaptive Kriging method based on K-means clustering and sampling in n-Ball (AK-KBⁿ).

The performance of AK-KBⁿ is evaluated through several numerical examples. According to the generated results, all the proposed learning functions are capable of guiding the search toward sample points close to the LSS in the critical region and result in a converged Kriging model that perfectly matches the true one in the regions of interest. The AK-KBⁿ method is demonstrated to be well suited for structural reliability analysis and a very good performance is observed in the investigated examples.

In this study, the statistical information of Kriging prediction, the relative contribution of the sample points to the failure probability and the distances between the candidate samples and the existing ones are all integrated into the proposed learning functions, which enables effective selection of informative samples for updating the Kriging model. Moreover, the number of required iterations is reduced by introducing the parallel computing strategy, which can dramatically alleviate the computation cost when time demanding numerical models are involved in the analysis.

Reliability-based design optimizations (RBDOs) of engineering structures involve complex non-linear/non-differentiable performance functions, including both continuous and discrete variables. The gradient-based RBDO algorithms are less than satisfactory for these cases. The simulation-based approaches could also be computationally inefficient, especially when the double-loop strategy is used. This paper aims to present a pseudo-double loop flexible RBDO, which is efficient for solving problems, including both discrete/continuous variables.

The method is based on the hybrid improved binary bat algorithm (BBA) and weighed simulation method (WSM). According to this method, each BBA’s movement generates proper candidate solutions, and subsequently, WSM evaluates the reliability levels for design candidates to conduct swarm in a low-cost safe-region.

The accuracy of the proposed enhanced BBA and also the hybrid WSM-BBA are examined for ten benchmark deterministic optimizations and also four RBDO problems of truss structures, respectively. The solved examples reveal computational efficiency and superiority of the method to conventional RBDO approaches for solving complex problems including discrete variables.

Unlike other RBDO approaches, the proposed method is such organized that only one simulation run suffices during the optimization process. The flexibility future of the proposed RBDO framework enables a designer to present multi-level design solutions for different arrangements of the problem by using the results of the only one simulation for WSM, which is very helpful to decrease computational burden of the RBDO. In addition, a new suitable transfer function that enhanced convergence rate and search ability of the original BBA is introduced.

This study aims to investigate and analyze the factors affecting the probable failure of rural entrepreneurs so that the most important factors responsible for failure in the business of small and local entrepreneurs are identified.

The present survey was conducted through the descriptive-analytical method by using a researcher-made questionnaire. The statistical population of the study included 1,641 greenhouse owner entrepreneurs in five rural communities. To clarify the key criteria affecting probable failure of greenhouse businesses, LISREL 8.8 computer software was used and the effects of selected indices on the process of probable failure of entrepreneurs were assessed using stepwise regression in the SPSS computer application environment.

According to the results, individual and managerial skills factors, deterrent financial and legal issues, social barriers and infrastructural issues investigated in this study were of the first to the fourth priorities in clarifying factors affecting probable failure of greenhouse businesses. Considering the intragroup relations in these factors, it could be said that individual and managerial skills factors and infrastructural issues had the highest correlation coefficient which could be attributed to individual and management weaknesses of entrepreneurs in understanding infrastructural issues as the most important parameters to be considered in starting businesses.

So far, few studies analyzed the failure of rural entrepreneurs and evaluated the probable factors affecting it. Thus, the present study is among the earliest instances in the field and its results could be of great benefit to domestic entrepreneurs and similar cases in other countries.

To quantify water closet (WC) provisions in shopping malls in order to help building professionals to determine effective sanitary designs at certain service standards in terms of the user's probable waiting time.

The proposed WC provision takes account of the probable waiting time corresponding to certain demand patterns of shopping malls. The probable waiting time for a WC and the failure rate of the closet in providing immediate service to the users at various WC provision levels described by a simple queuing process are evaluated by the Monte Carlo simulations. Model parameters such as the maximum waiting time expected by the users, the frequency distributions of the time between user arrivals and the service time at sanitary facilities were determined from a survey of a large shopping mall in Hong Kong.

The suitable provision of WCs was determined by the user's acceptable waiting time, and compared with those provision levels determined by the limiting failure rate of providing immediate service.

The model parameters are not exhaustive, with assumptions made for the queuing process of washroom users and have only been determined from a recent survey in Hong Kong, which perhaps will limit the model's usefulness elsewhere.

A useful source of reference in planning the sanitary facilities of shopping malls for various user demands. The methodology can be used in a modified form for most building types.

This paper proposes mathematical expressions for WC provision in shopping malls and presents a template to determine the required model parameters. The model offers practical help to professionals involved in planning, designing and managing the sanitary facilities of shopping malls.

Describes a study to measure the quality of service provided by food‐poisoning surveillance agencies in England and Wales in terms of the requirements of a representative consumer ‐ the egg producing industry ‐ adopting “egg associated” outbreak investigation reports as the reference output. Defines and makes use of four primary performance indicators: accessibility of information; completeness of evidence supplied in food‐poisoning outbreak investigation reports as to the sources of infection in “egg‐associated” outbreaks; timeliness of information published; and utility of information and advice aimed at preventing or controlling food poisoning. Finds that quality expectations in each parameter measured are not met. Examines reasons why surveillance agencies have not delivered the quality demanded. Makes use of detailed case studies to illustrate inadequacies of current practice. Attributes failure to deliver “accessibility” to a lack of recognition on the status or nature of “consumers”, combined with a self‐maintenance motivation of the part of the surveillance agencies. Finds that failures to deliver “completeness” and “utility” may result from the same defects which give rise to the lack of “accessibility” in that, failing to recognize the consumers of a public service for what they are, the agencies feel no need to provide them with the data they require. The research indicates that self‐maintenance by scientific epidemiologists may introduce biases which when combined with a politically inspired need to transfer responsibility for food‐poisoning outbreaks, skew the conduct of investigations and their conclusions. Contends that this is compounded by serious and multiple inadequacies in the conduct of investigations, arising at least in part from the lack of training and relative inexperience of investigators, the whole conditioned by interdisciplinary rivalry between the professional groups staffing the different agencies. Finds that in addition failures to exploit or develop epidemiological technologies has affected the ability of investigators to resolve the uncertainties identified. Makes recommendations directed at improving the performance of the surveillance agencies which, if adopted will substantially enhance food poisoning control efforts.

Customer reaction to failure is of essential importance and varies by level of involvement with products and services. Thus, the purpose of this paper is to use the FCB grid to examine effects of involvement and emotion on failure of products and services. It also explores effects of negative word-of-mouth, consumer advocacy, customer voicing and gender on the so-called silent killers.

A 2 (male or female)×4 (high and low involvement, feelings, thinking in FCB grid) between-subjects experiment on 311 college students, who have recently experienced product failure, is performed.

Results reveal that customers with different levels of involvement react differently to product failure. Furthermore, low-involvement products are more likely to develop silent killers. The results also show that silent killer is more common among men.

To the best of the authors’ knowledge, no similar study is performed on the relationship between involvement and failure of products or services. In addition, this attempt is the first quantitative study to examine the phenomenon of silent killers in this field.