The blade shape parameters have a remarkable effect on the centrifugal pump performance. In order to reveal the relationship between these parameters and pump performance, a single channel was regarded as the research object to calculate its performance by numerical simulation, and the performance was measured on an experimental rig. The optimized ANN is proposed, and it is proved to be highly accurate. The ANN correlation coefficient of the total response could be above 0.997 after thousands of retaining. The sorts and degrees affecting performance parameters were found out by gray relation analysis. It was found that the blade angles at the leading edge were more influential for reaction force, head and minimum pressure, while the wrap angles had greater impact for efficiency. Furthermore, a multiple linear regression model was established to quantify the weight and trend of the influence of blade shape parameters on performance. The results provide a reference guide for the optimized design of centrifugal impeller to improve pump performance.

Modelling is an effective way of designing, understanding, and analysing bio-refinery supply chain systems. The supply chain is a complex process consisting of many systems interacting with each other. It requires the modelling of the processes in the presence of multiple autonomous entities (i.e. biomass producers, bio-processors and transporters), multiple performance measures and multiple objectives, both local and global, which together constitute very complex interaction effects. In this paper, simulation models for recovering biomass from the field of the biorefinery are developed and validated using some industry data and the minimum biomass recovery cost is established based on different strategies employed for recovering biomass. Energy densification techniques are evaluated for their net present worth and the technologies that offer greater returns for the industry are recommended. In addition, a new scheduling algorithm is also developed to enhance the process flow of the management of resources and the flow of biomass. The primary objective is to investigate different strategies to reach the lowest cost delivery of sugarcane harvest residue to a sugar factory through optimally located bio-refineries. A simulation /optimisation solution approach is also developed to tackle the stochastic variables in the bioenergy production system based on different statistical distributions such as Weibull and Pearson distributions. In this approach, a genetic algorithm is integrated with simulation to improve the initial solution and search the near-optimal solution. A case study is conducted to illustrate the results and to validate the applicability for the real world implementation using ExtendSIM Simulation software using some real data from Australian Mills.

COVID-19 has caused severe disruptions in global economic activities, and its impacts on stock markets cannot be overemphasized. The study employs market model and event study approach with four events (WHO announcement of COVID-19 as a global health emergency, confirmed infections, confirmed deaths, and vaccination) to examine the reactions of four African regional blocs’ markets to the pandemic from September 1, 2019, to August 31, 2021, to estimate the average abnormal returns of each regional bloc. On the day of the WHO announcement, we document insignificant negative average abnormal returns in the Northern bloc. We also document significant negative average abnormal returns for infections in all but the Northern bloc on the event day. The Western bloc generated the highest significant negative average abnormal return (-43 per cent) on the day COVID-19 death was confirmed on the continent. We finally document insignificant average abnormal returns from weeks 1 to 20 after the first vaccination in the Northern and Eastern blocs. The study recommends that investors, portfolio managers, and speculators not panic during similar pandemics since they can generate significant abnormal returns and diversify their investment holdings across the four regional blocs in Africa, as demonstrated by the COVID-19 pandemic.

In Australia, Bioenergy plays an important role in modern power systems, where many biomass resources provide greenhouse gas neutral and electricity at a variety of scales. By 2050, the Biomass energy is projected to have a 40-50 % share as an alternative source of energy. In addition to conversion of biomass, barriers and uncertainties in the production, supply may hinder biomass energy development. The sugarcane is an essential ingredient in the production of Bioenergy, across the whole spectrum ranging from the first generation to second generation, e.g., production of energy from the lignocellulosic component of the sugarcane initially regarded as waste (bagasse and cane residue). Sustainable recovery of the Lignocellulosic component of sugarcane from the field through a structured process is largely unknown and associated with high capital outlay that have stifled the growth of bioenergy sector. In this context, this paper develops a new scheduler to optimise the recovery of lignocellulosic component of sugarcane and cane, transport and harvest systems with reducing the associated costs and operational time. An Optimisation Algorithm called Limited Discrepancy Search has been adapted and integrated with the developed scheduling transport algorithms. The developed algorithms are formulated and coded by Optimization Programming Language (OPL) to obtain the optimised cane and cane residues transport schedules. Computational experiments demonstrate that high-quality solutions are obtainable for industry-scale instances. To provide insightful decisions, sensitivity analysis is conducted in terms of different scenarios and criteria.

This paper studies the problem of scheduling a finite set of customers with stochastic service times for a single-server system. The objective is to minimize the waiting time of customers, the idle time of the server, and the lateness of the schedule. Because of the NP-hardness of the problem, the optimal schedule is notoriously hard to derive with reasonable computation times. Therefore, we develop a simulation based K-steps look-ahead selection method which can result in nearly optimal schedules within reasonable computation times. Furthermore, we study the different distributed service times, e.g., Exponential, Weibull and lognormal distribution and the results show that the proposed algorithm can obtain better results than the lag order approximation method proposed by Vink et al. (2015) [Vink, W., Kuiper, A., Kemper, B., & Bhulai, S. (2015). Optimal appointment scheduling in continuous time: The lag order approximation method. European Journal of Operational Research, 240(1), 213-219.]. Finally, a realistic appointment scheduling includes experiments to verify the good performance of the proposed method.

This study uses an alternative fabrication scheme to study the effect of rework of nonconforming items and delayed differentiation on a multiproduct supply-chain system. Traditional economic production quantity model focuses on a single-product inventory system where all products made are assumed to be perfect quality and finished products are issued continuously. To increase machine utilization, lower quality costs in production, and reflect the real-world vendor-buyer integrated systems Chiu et al. (2016a) [Chiu, Y-S.P., Kuo, J-S., Chiu, S. W., Hsieh, Y-T. (2016a). Effect of delayed differentiation on a multiproduct vendor–buyer integrated inventory system with rework. Advances in Production Engineering & Management, 11(4), 333-344.] employed a single-machine two-stage production scheme to study the effects of rework and delayed differentiation on a multi-product supply-chain system. With the intention of further reducing fabrication cycle time, this study considers an alternative two-machine two-stage fabrication scheme to re-explore the problem in Chiu et al. (2016a). Machine one solely produces all common parts for multiple end products. Then, machine two fabricates the customized multiproduct using a common cycle time strategy. Through the use of mathematical modeling and analyses, the optimal production cycle length and distribution policy are derived. Numerical examples are provided to demonstrate practical usage of the research results, and show its significant benefit in reducing fabrication cycle time compared to that obtained from prior studies that used different schemes.

Motivated by a practical situation in a digital transformation project, this paper considers a resource-constrained project scheduling problem with multiple modes, multiple skill types, and differentiated professional capabilities. In the proposed problem, each project activity has one or more alternative execution modes associated with a trade-off between processing time and resource consumption. In an execution mode, an activity requires a certain number of employees with specific skill types and required professional capabilities. A mixed integer programming model is developed to minimize the total project duration. Since this problem is NP-hard, an efficient immunoglobulin-based artificial immune system (EIAIS) algorithm with a new encoding and decoding scheme and novel components is proposed. The effectiveness of the proposed EIAIS algorithm is tested on randomly generated instances. Computational results show that the proposed EIAIS algorithm has better performance than the existing algorithms.

An effective operations of a projection spot welding (PSW) machine is closely related to the effec-tiveness of the maintenance. Timely maintenance can prevent failures and improve reliability and maintainability of the machine. Therefore, establishing the maintenance frequency for the welding machine is one of the most important tasks for plant engineers. In this regard, reliability analysis of the welding machine can be used to establish preventive maintenance intervals (PMI) and to identify the critical parts of the system. In this reliability and maintainability study, analysis of the PSW machine was carried out. The failure and repair data for analysis were obtained from automobile manufacturing company located in Uzbekistan. The machine was divided into three main sub-systems: electrical, pneumatic and hydraulic. Different distributions functions for all sub-systems was tested and their parameters tabulated. Based on estimated parameters of the analyzed distribu-tions, PMI for the PSW machines sub-systems at different reliability levels was calculated. Finally, preventive measures for enhancing the reliability of the PSW machine sub-systems are suggested.

The purpose of this study was to investigate the mediating role of total quality management (TQM) between entrepreneurial orientation (EO) and SME export performance in the manufacturing sector of Pakistan. This study was originated from the fact that only a few studies have examined on how the firm’s intangible resources and capabilities such as EO and TQM drive SMEs’ export performance. Some questionnaires in Likert scale were used to collect the data and 364 usable responses were received from the owner/managers of exporting SMEs. Partial Least Squares Structural Equation Modeling (PLS-SEM) was used for the data analysis. The findings reveal significant relationship between EO and TQM with SME export performance. Furthermore, this study found the complementary mediating role of TQM between EO and SME export performance of manufacturing sector of Pakistan. This study has implications for owner/managers of SMEs. The results offer a better understanding regarding EO and TQM implementation to SMEs owner / managers. Thus, owner/managers of SMEs can take better decisions for the implementation of TQM practices. Furthermore, to the best of researcher’s knowledge, this study is the first work, which examines Pakistan`s SMEs export performance in association with the TQM as the mediating factor between EO and SME export performance.

This paper has been retracted.

In the domain of international construction projects, managing supply chains presents distinct challenges due to the intricate task of coordinating multiple stakeholders within diverse cultural, economic, and regulatory contexts. Prior research highlights the significance of incentive mechanisms and collaborative procurement practices, yet the effectiveness of these strategies in augmenting performance for international projects has not been extensively examined. This investigation explores the effects of financial and non-financial incentives on the performance of global construction projects, with a focus on the mediating role of cooperation. Data were gathered from Chinese international contractors and local suppliers and subsequently analyzed using Structural Equation Modeling. The results reveal two separate pathways of influence. Firstly, financial incentives exhibited substantial direct and indirect impacts on project performance; secondly, while non-financial incentives did not directly affect project performance, they significantly impacted cooperation levels, which in turn mediated the relationship between non-financial incentives and project performance. This study provides essential perspectives for managing international construction projects, emphasizing the critical need for the combined application of financial and non-financial incentives to foster cooperation and ultimately achieve superior project outcomes.