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This paper aims to develop a system dynamics (SD) model to identify causal relationships among the elements of failure modes and effects analysis (FMEA), i.e. failure modes, effects and causes.

A causal loop diagram (CLD) has been developed based on the results obtained from interdependencies and correlations analysis among the FMEA elements through applying the integrated approach of FMEA-quality function deployment (QFD) developed by Shaker et al. (2019). The proposed model was examined in a steel manufacturing company to identify and model the causes and effects relationships among failure modes, effects and causes of a roller-transmission system.

Findings indicated interactions among the most significant failure modes, effects and causes. Moreover, corrective actions defined to eliminate or relieve critical failure causes. Consequently, production costs decreased, and the production rate increased due to eliminated/decreased failure modes.

The application of CLD illustrates causal relationships among FMEA elements in a more effective way and results in a more precise recognition of the root causes of the potential failure modes and their easy elimination/decrease. Therefore, applying the proposed approach leads to a better analysis of the interactions among FMEA elements, decreased system's failure rate and increased system availability.

The literature review indicated a few studies on the application of SD methodology in the maintenance area, and no study was performed on the causal interactions among FMEA elements through an FMEA-QFD based SD approach. Although the interactions of these elements are significant and helpful in risks ranking, researchers fail to investigate them sufficiently.

The purpose of this paper is to propose an integrative approach for improving failure modes and effects analysis (FMEA).

An extensive literature review on FMEA has been performed. Then, an integrative approach has been proposed based on literature review. The proposed approach is an integration of FMEA and quality function deployment (QFD). The proposed approach includes a two-phase QFD. In the first phase, failure modes are prioritized based on failure effects and in the second phase, failure causes are prioritized based on failure modes. The proposed approach has been examined in a case example at the blast furnace operation of a steel-manufacturing company.

Results of the case example indicated that stove shell crack in hot blast blower, pump failure in cooling water supply pump and bleeder valves failed to operate are the first three important failure modes. In addition, fire and explosion are the most important failure effects. Also, improper maintenance, over pressure and excess temperature are the most important failure causes. Findings also indicated that the proposed approach with the consideration of interrelationships among failure effects, failure mode and failure causes can influence and adjust risk priority number (RPN) in FMEA.

As manufacturing departments are mostly dealing with failure effects and modes of machinery and maintenance departments are mostly dealing with causes of failures, the proposed model can support better coordination and integration between the two departments. Such support seems to be more important in firms with continuous production lines wherein line interruption influences response to customers more seriously. A wide range of future study opportunities indicates the attractiveness and contribution of the subject to the knowledge of FMEA.

Although the literature indicates that in most of studies the outcomes of QFD were entered into FMEA and in some studies the RPN of FMEA was entered into QFD as importance rating, the proposed approach is a true type of the so-called “integration of FMEA and QFD” because the three main elements of FMEA formed the structure of QFD. In other words, the proposed approach can be considered as an innovation in the FMEA structure, not as a data provider prior to it or a data receiver after it.

This study aimed to evaluate the cytotoxic/apoptotic effects of sweet apricot kernel ethanolic extract (SAEE) on human cancerous PANC-1 and 293/KDR normal cells.

The extract was prepared by maceration, and its chemical composition was analyzed by gas chromatography-mass spectrometry (GC-MS). The biological effects of SAEE on PANC-1 and 293/KDR cells were investigated using MTT (3–(4, 5-dimethylthiazole-2-yl)-2,5-diphenyl tetrazolium bromide) assay, DAPI (4',6-diamidino-2-phenylindole) and AnnexinV/propidium iodide (PI) staining. The expression of pro- and anti-apoptotic genes was evaluated by real-time quantitative polymerase chain reaction (real-time q-PCR) analysis.

The SAEE showed the selective growth inhibitory activity against PANC-1 cells with an IC50 (the 50% inhibitory concentration) value of about 1 mg/mL at 72 h. Further investigations by DAPI staining and flow cytometry revealed nucleus fragmentation and elevation of apoptotic cells, respectively. Also, a significant decrease in B-cell lymphoma 2 (Bcl-2)/Bcl-2-associated x protein (Bax) ratio (0.41, p = 0.001) and the up-regulation of caspase-3 expression (1.5 fold, p = 0.002) indicated the induction of apoptosis in PANC-1 cells but not in 293/KDR non-cancerous cells. These results suggest that SAEE could induce apoptosis in cancer cells via a mitochondrial dependent pathway. Furthermore, GC-MS analysis showed that the SAEE is rich in γ-sitosterol and γ-tocopherol. Overall, the findings suggest that because of the selective impacts of SAEE on PANC-1 cells, it can be considered as a supportive care in adjuvant therapy for pancreatic cancer. However, the potent anticancer effects of main components of SAEE and its clinical value as an antitumor drug should be further investigated.

Considerable limitations of this study were that the related mechanisms of selective impacts of SAEE on cancerous and normal cells and potent cytotoxic/apoptotic effects of γ-sitosterol and γ-tocopherol as major components of SAEE were not investigated.

Recently, a growing interest has been dedicated to plant-based natural products. Sweet apricot kernel exerts a number of pharmacological activities; however, the anticancer effect, related mechanisms and its active compounds were rarely investigated. In this study, the authors aimed to evaluate the cytotoxic/apoptotic effects of SAEE on human cancerous PANC-1 and 293/KDR normal cells.

In recent years, research on children's tourism experiences has gained prominence, as children are becoming an increasingly vital market for the tourism industry. While events are a main sector of the industry and host millions of children every year, there is a lack of research specifically focussed on children's experiences in events. This chapter focusses on children's entertainment events which can provide children with a satisfying, memorable and educational experience. This study has developed a framework to facilitate deeper mixed studies on children's experiences in event tourism. The framework is composed of four pillars based on various social, tourism and event theories and models, including the Cognition–Affect–Behaviour (CAB) theoretical framework, the Orchestra Model of Experience, the Event Experience Scales (EES), the Theory of Child Well-being and the Transtheoretical Model of Behaviour Change (TTM). The framework can be used by future researchers as an analytical evaluation tool to study children's experiences in different types of events and understand the mechanisms of behaviour change in this context.

Untimely responses to emergency situations in urban areas contribute to a rising mortality rate and impact society's primary capital. The efficient dispatch and relocation of ambulances pose operational and momentary challenges, necessitating an optimal policy based on the system's real-time status. While previous studies have addressed these concerns, limited attention has been given to the optimal allocation of technicians to respond to emergency situation and minimize overall system costs.

In this paper, a bi-objective mathematical model is proposed to maximize system coverage and enable flexible movement across bases for location, dispatch and relocation of ambulances. Ambulances relocation involves two key decisions: (1) allocating ambulances to bases after completing services and (2) deciding to change the current ambulance location among existing bases to potentially improve response times to future emergencies. The model also considers the varying capabilities of technicians for proper allocation in emergency situations.

The Augmented Epsilon-Constrained (AEC) method is employed to solve the proposed model for small-sized problem. Due to the NP-Hardness of the model, the NSGA-II and MOPSO metaheuristic algorithms are utilized to obtain efficient solutions for large-sized problems. The findings demonstrate the superiority of the MOPSO algorithm.

This study can be useful for emergency medical centers and healthcare companies in providing more effective responses to emergency situations by sending technicians and ambulances.

In this study, a two-objective mathematical model is developed for ambulance location and dispatch and solved by using the AEC method as well as the NSGA-II and MOPSO metaheuristic algorithms. The mathematical model encompasses three primary types of decision-making: (1) Allocating ambulances to bases after completing their service, (2) deciding to relocate the current ambulance among existing bases to potentially enhance response times to future emergencies and (3) considering the diverse abilities of technicians for accurate allocation to emergency situations.