Turning is the utmost elementary process among several CNC machine tool operations which is a versatile, efficient and widely used in industries including mechanical, aerospace and automotive sectors. Most frequently the manufacturing industries face the problem of cutting down the production cost without any oblation in the quality of products. Selection of process parameter is essential for assuring a quality product. Convenient choice of the cutting conditions, parameters and tools for the maximum Material removal rate (MRR) and surface finish needs a sophisticated approach adopting mathematical and statistical models as well as experimental method. Taguchi’s method is a very compelling tool to optimize the process variables. The intention of the present study is to determine surface roughness (Ra) and MRR which are key responses to justify the quality of turning operation. Four process parameters have been selected viz. Nose radius (NR), depth of cut (DOC), feed rate (FR) and spindle speed or cutting speed (CS) that influences these responses. During machining operations, the influence of the process parameters and their interac-tion have been analyzed using a statistical tool ANOVA. Aluminum alloy is widely acceptable by industries owing to its good strength to weight ratio, high resistance to corrosion, malleability and excellent resistance during elevated temperatures.

The purpose of the current study was to investigate the determinants of small and medium manu-facturing enterprises’ export performance empirically in the context of Pakistan. The study adopted survey method to collect forty-five (45) responses from small and medium manufacturing firms through E-mail survey. The study produced four determinants of SME export performance, such as entrepreneurial orientation (EO), total quality management (TQM), business network (BN) and export market orientation (EMO). Thus, internal consistency reliability and discriminant validity were examined of the study instruments through panel expert’s opinion and the small sample size was investigated using statistical software SPSS-21 and smartPLS-3. The results of the study con-firmed that scale reliability and validity and moreover, current study found a positive relationship between TQM and SME export performance. On the other hand, the study also found insignificant relationship between EO, BN, EMO and SME export performance. Furthermore, the study recommended future study should validate the current study research framework on large sample size.

Municipal solid waste management has become a global concern during the past decades in many countries such as Canada and waste management technological advancements and regula-tions have been increased. Solid wastes emit greenhouse gases which result in global climate change, pollution of air and water which has tremendous negative impact on human health. Due to the excessive urbanization and fast economic development, municipal solid wastes have been increased in developing countries. In order to manage this emerging issue, polluted countries need a series of legislations and policies toward solid wastes. Accurate prediction of future mu-nicipal solid waste generation plays a critical role for future planning. This paper focuses on mu-nicipal solid waste generation in city of Tehran, the most populated city in Middle East. Three methods are explored in this paper to analyze the past solid waste time-series analysis: regres-sion, Artificial Neural Network (ANN) and Adaptive Neuro-Fuzzy Inference System (ANFIS). The first method, which is the classical regression approach, is used as a baseline for considered neural networks models. The second method utilizes the past data as training example of neural network to find autocorrelation among target; lastly, the neuro-fuzzy learns the relation of data using fuzzy-rule. Mean Absolute Percentage Error (MAPE) metric is used to evaluate the per-formance. Finally, analysis of variance (ANOVA) and Duncan experiment are performed to ver-ify and validate the outcome of the experiments.