Quality of blast preparation for rock beneficiation influences both on integrity of mineral stock in particular and in economical performances of enterprise operations in general. While rock processing for obtaining of crushed stone the yield of screenings is high, its amounts depend on rock strength properties. Investigation into the influence of drilling and blasting parameters on strength properties of blasted rocks is an urgent research and practical task for mining companies producing building stones. This article discusses results of full-scale experiment aimed at determination of strength of blasted rocks in shotpile with accounting for fracture zones as a function of rock massif saturation with energy of explosive substance.

In this study, a multi-product, multi-period and non-linear programming model is developed for production planning problem where demand is under uncertainty. The proposed study is designed for a real-world case study of chemicals production factory with 1 production line and 2 manual and automatic technologies. In manual technology, workers are working with 3 amateur, typical and professional skills in 2 typical and overtime working. Automatic technology in this system has n machines in which the repairing and maintenance of the machineries are also included. This system has n products and the products are life-limited and with diversity. The primary goal is to propose a model for improvement of the production planning and minimization of the production system costs. The products in high volume and various types are produced and they are stored in bottles as the final products. For different production periods, the human forces capacities are considered and the level of employment or forces dismissal are considered. The production process is forwarding and backward process is not acceptable; that is, it is not allowable to rework in this system. Delivering final product from stockpiles to the retailers is conducted using vehicles with limited capacity. To solve the model in larger space and because of the complexity of the model, meta-heuristic algorithm is used. Finally, it is concluded that due to covering most of the assumptions in perishable products production, the proposed model is closer to the real-world circumstances and reduces costs in production systems.

In the present study, the flexural behavior of concrete beams reinforced with longitudinal rebars made of glass fiber reinforced polymer composites (GFRP), is studied using finite element method. For this purpose, a number of concrete beams with square sections are modeled in ABAQUS. In all of the beams, four GFRP rebars with diameter of 12 mm, and 10 steel rebars with diameter of 8 mm are vertically used to prevent creating shear cracks in the beams. The beam no. 1 is without transverse rebar, beam no. 2 has a row of transverse rebar, which is placed at the bottom and in the plane of vertical rebars. Beam no. 3 has a row of transverse rebars that is placed at the top and in the plane of vertical rebars; and the beam no. 4 has two rows of transverse rebar at the top and bottom of the beam in the plane of vertical rebars. The beams are gradually loaded under up to 6 ton, and the amounts of displacement and strain at the middle of beams are compared together. The obtained results reveal that the force-displacement diagram of reinforced beams with composite rebars are almost linear until ultimate phase, and in all of the beams, adding transverse rebar leads to less deflection in the middle of the beam under an identical loading. Moreover, the load bearing capacity of beams containing transverse rebars, were higher than the other beams.

This paper focuses on the impact of fear emotion upon technology adoption by educators and students during Covid-19 pandemic. Mobile learning (m-learning) has been applied as the educational social platform within higher education institutes, public as well as private. The research hypotheses were associated with the Covid-19 influence on m-learning adoption with the rise of the coronavirus increasing types of fear. Such fears include fear caused by the education failure, family lockdown, and loss of social relationships. Teachers and students are mostly fearful of these aspects of the situation. An integrated model was established within the research, using theoretical models; the Planned Behavior theory, the Technology Acceptance Model, and the Expectation-Confirmation Model. The proposed integrated model (using PLS-SEM software) was analyzed using an online survey data, with 420 respondents from Zayed University, UAE. The findings indicated that attitude was the best predictor for using the m-learning system, followed by continuous intention, expectation confirmation, perceived usefulness, ease-of-use, perceived fear, behavioral control, and satisfaction. According to the research, during the coronavirus pandemic, if the m-learning system is adopted for educational reasons, the learning and teaching outcome proves quite promising. Yet there is a fear of the family being stressed, or of loss of friends, and also a fear of the results of future schooling. It is therefore necessary to assess the students efficiently during this pandemic so that the situation can be managed emotionally.

Extension of product’s useful life through product recovery options can help to reduce the consumption of natural resource and environmental pollution. Remanufacturing operation is considered as the most suitable product recovery option for automotive parts. The objective of this paper is to identify the barriers and the critical success factors in automotive engine remanufacturing. A case study is carried out in an automotive engine remanufacturing plant, situated in the south-western part of India. In this case study, the strategic, tactical and operational characteristics of the remanufacturing process are explored, what are the barriers they have faced while remanufacturing and to overcome those barriers, what strategies they have adopted are also analyzed. A fuzzy technique for order performance by similarity to ideal solutions (TOPSIS) is used to identify the critical success factor to overcome the roadblocks of remanufacturing. As this study is directed by the experts’ opinion from the remanufacturing plant which proves its practical implication. This case study is also useful for the other OEM remanufacturers in India.

Many researchers focused on economic production quantity (EPQ) model for deteriorating items with rework of defective items in a single production run. Few of them proposed the model for multi-production inventory model under the assumptions (i) all the defective items can be reproduced as serviceable items and (ii) all the deteriorating items can be detached from the inventory through screening process. However, in real life manufacturing systems, due to controllable or uncontrollable factors, the defective items may not be reproduced as serviceable items and hence the generation of scrap (disposable) items is potential. It is possible that the internally deteriorating items like fruits, vegetables, eggs, pharmaceutical drugs, etc. pass on to customers which will make negative impact on corporate image in the global market. This paper presents a multi-production run inventory model for deteriorating items with scrap, defective items, failure rework and penalty cost for selling the deteriorating items to customers under finite planning horizon. Our objective is to determine the optimal production run, optimal finite planning horizon by minimizing the total cost of the system. A solution procedure with an algorithm is proposed and a numerical example is provided to demonstrate the applicability of the model. Finally, sensitivity analysis is provided to provide managerial phenomena of the system.

The purpose of this study is to analyze the effect of customization purchase intention of Smartphones, entertainment, interaction, social media marketing, trendiness, and Word-of-Mouth on purchase intention of Smartphones. The study uses a quantitative method by distributing online questionnaires to 217 consumers in Banten Indonesia and the method of distributing questionnaires is a snowball sampling system. Data processing and testing of hypotheses and models in this study are based on Structural Equation Modeling (SEM). The research has benefits in increasing knowledge and information for companies about the importance of brand awareness through increasing influencing factors such as social media marketing and word of mouth. Based on the results of SmartPLS analysis, Interaction, Word-of-Mouth, Social media marketing, Entertainment and Trendiness have insignificant effects on purchase intentions of Smartphones while Customization has significant effects on purchase intentions of Smartphones during.

Customers are financial and intellectual capital of the firm and its survival and success depend on the attitude and firm performance to its customers. The goal of this article is to study customer satisfaction in Bonny Chow National Distribution Company and offering a model to evaluate customer satisfaction and also to study strength and weakness to improve and facilitate the defects. This study is descriptive, because it collects data and analyzes hypothesis based on expert survey. The questionnaire used in this paper has 10 questions on measure customer satisfaction. The results show that responders were satisfied with the visitors and delivery personnel and they were dissatisfied with the firm. In other words hypothesis 1 and 2 were accepted and hypothesis 3 was rejected.

The development of technology and information has influenced people's lifestyles in making purchases from conventional to online shopping. Research on online marketing has become an interest in academics and practitioners in recent years. Measurement for e-service quality in this study will be reconstructed based on a review on previous conceptual and empirical literature. The purpose of this research is to build customer e-service through the reconstruction of e-service quality dimensions. The research uses cross-section data with geographically dispersed location of users of online travel services in the region of Indonesia. Model testing is performed using structural equation modeling with a sample count of 262 respondents. The analysis results show that the efficiency and incentive dimensions meet the creation of the e-service quality construct.

Fashion and Apparel Supply Chains work in a very fast-changing environment and always demand better quality, higher availability of products, broader assortments and shorter delivery times. An efficient Supply Chain Management can make a difference between success and failure in the market. In this context, the main purposes of the presented work are: (i) to define the physical and informative flows, together with connected cost and revenue items, which characterize a Fashion Supply Chain working with a wide network of direct-operated or franchising mono-brand stores and (ii) to optimize Supply Chain performances through a responsive approach which, during the sales season, analyses actual market demand and adjusts operations plans accordingly. The framework aims at becoming a decision support system for the optimization of the performances of a process that starts from the development of the collection by the Styling Office and ends with the withdrawal of unsold items from the stores. In order to analyze the performances under different scenarios, a set of Key Performance indicators, partially selected from the SCOR Model, is defined.