The boom of real estate has been a motivating force for economic growth in India for the past few years. However, the Real Estate (RE) market of India is still in the embryonic phase and juvenile. In the context of the real estate projects, it is a general situation observed that such projects cannot meet the target as the Indian real estate companies are deficient in scientific management technology to confront the risks. The research paper aims to focus mainly on constraints and demurral of Risk Management (RM) in RE firms of India to investigate findings for the same in the Indian Real estate market and further focusing on RE projects of Ahmedabad. The paper is mostly founded on an overview of individuals who are straightforwardly or firmly identified with the administration and the RE business in India. The questionnaire survey shall be targeted over the five prime territories of Ahmedabad. This research further highlights to concerned identified primary critical risk factors (by Criticality Index Method) influencing the residential real estate market and then developing a framework for assessing the factors carrying out the quantitative analysis using various analytical methods of SPSS software, Factor analysis, ANOVA and Post-Hoc Test. The validation of the results has been done through a survey of experienced experts. The critical risks identified based on the questionnaire survey are modeled through the decision tree diagram.

In today’s scenario, software has become an essential component in all kinds of systems. The size and the complexity of the software increases with a corresponding increase in its functionality, hence leads to the development of the modular software systems. Software developers emphasize on the concept of component based software engineering (CBSE) for the development of modular software systems. The CBSE concept consists of dividing the software into a number of modules; selecting Commercial Off-the-Shelf (COTS) for each module; and finally integrating the modules to develop the final software system. The selection of COTS for any module plays a vital role in software development. To address the problem of selection of COTS, a framework for ranking and selection of various COTS components for any software system based on expert opinion elicitation and fuzzy-based matrix methodology is proposed in this research paper. The selection problem is modeled as a multi-criteria decision making (MCDM) problem. The evaluation criteria are identified through extensive literature study and the COTS components are ranked based on these identified and selected evaluation criteria using the proposed methods according to the value of a permanent function of their criteria matrices. The methodology is explained through an example and is validated by comparing with an existing method.

Global competition in the marketing has led organizations to be more responsive and efficient to the customers’ needs through quick-new product development and minimized delivery time. Customer satisfaction becomes the major issue for organizations; therefore organizations focus more and more on the collaborative supply chain. Thus, supply chain collaboration has become a major success factor for the organizations to achieve their corporate goals. The current research study is an attempt to address the supply chain collaboration through a systematic literature review. In findings, various specific areas have been examined to understand the necessity, evolution, issues and challenges, types, drivers, benefits, and barriers in the context of supply chain collaboration. Further, the research gap and future agenda have been derived which is very helpful for academics and practitioners to understand supply chain collaboration, gaps in the literature, and future agenda about the supply chain collaboration.

Scheduling ‘n’ jobs on ‘m’ machines in a flow shop is NP- hard problem and places itself at prominent place in the area of production scheduling. The essence of any scheduling algorithm is to minimize the makespan in a flowshop environment. In this paper an attempt has been made to develop a heuristic algorithm, based on the reduced weightage of machines at each stage to generate different combination of ‘m-1’ sequences. The proposed heuristic has been tested on several benchmark problems of Taillard (1993) [Taillard, E. (1993). Benchmarks for basic scheduling problems. European Journal of Operational Research, 64, 278-285.]. The performance of the proposed heuristic is compared with three well-known heuristics, namely Palmer’s heuristic, Campbell’s CDS heuristic, and Dannenbring’s rapid access heuristic. Results are evaluated with the best-known upper-bound solutions and found better than the above three.

In this paper, we consider the inventory model for perishable items with quadratic trapezoidal type demand rate, that is, the demand rate is a piecewise quadratic function under constant deterioration rate. The model consider allows for shortages and the demand is partially backlogged. The model is solved analytically by minimizing the total inventory cost. The result is illustrated with numerical example. Finally, we discuss sensitivity analysis for the model.

In the present day, focused commercial centers, offering exchange credit, have turned into a usually received strategy. Past inventory models under reasonable postponement in installments generally accepted that the request of the things was either consistent or simply relying on the retail cost. In this paper, we proposed to sum up, two distribution centers inventory model for crumbling things when the provider offers the retailer to defer period and thus the retailer gives to postpone period to their clients. The request design has been figured in a powerful example, which can be communicated in a straight or exponential shape. Shortages were not permitted. The differing criteria and lead time, smashing expenses were thought to be constant elements of unit cost and lead time, separately. From these, a basic iterative calculation to acquire the ideal renewal number and time booking was given. At last, numerical cases were introduced to show the model and investigation of different parameters was additionally performed. Likewise, the impact of changes in the diverse parameters in the ideal aggregate cost was graphically displayed and the suggestions were examined in details.

The present paper deals with the development of prediction model using response surface methodology and artificial neural network and optimizes the process parameter using 3D surface plot. The experiment has been conducted using coated carbide insert in machining AISI 1040 steel under dry environment. The coefficient of determination value for RSM model is found to be high (R2 = 0.99 close to unity). It indicates the goodness of fit for the model and high significance of the model. The percentage of error for RSM model is found to be only from -2.63 to 2.47. The maximum error between ANN model and experimental lies between -1.27 and 0.02 %, which is significantly less than the RSM model. Hence, both the proposed RSM and ANN prediction model sufficiently predict the surface roughness, accurately. However, ANN prediction model seems to be better compared with RSM model. From the 3D surface plots, the optimal parametric combination for the lowest surface roughness is d1-f1-v3 i.e. depth of cut of 0.1 mm, feed of 0.04 mm/rev and cutting speed of 260 m/min respectively.

Electrical Discharge Machining (EDM) is one of the most basic non-conventional machining processes for production of complex geometries and process of hard materials, which are difficult to machine by conventional process. It is capable of machining geometrically complex or hard material components, that are precise and difficult-to-machine such as heat-treated tool steels, composites, super alloys, ceramics, carbides, heat resistant steels etc. The present study is focusing on the die sinking electric discharge machining (EDM) of AISI H 13, W.-Nr. 1.2344 Grade: Ovar Supreme for finding out the effect of machining parameters such as discharge current (GI), pulse on time (POT), pulse off time (POF) and spark gap (SG) on performance response like Material removal rate (MRR), Surface Roughness (Ra) & Overcut (OC) using Square-shaped Cu tool with Lateral flushing. A well-designed experimental scheme is used to reduce the total number of experiments. Parts of the experiment are conducted with the L9 orthogonal array based on the Taguchi methodology and significant process parameters are identified using Analysis of Variance (ANOVA). It is found that MRR is affected by gap current & Ra is affected by pulse on time. Moreover, the signal-to-noise ratios associated with the observed values in the experiments are determined by which factor is most affected by the responses of MRR, Ra and OC. These experimental data are further investigated using Grey Relational Analysis to optimize multiple performances in which different levels combination of the factors are ranked based on grey relational grade. The analysis reveals that substantial improvement in machining performance takes place following this technique.

Friction Stir Welding (FSW) is a relatively new solid state joining technique which is used not only for joining the aluminum and its alloys but also has potential for joining dissimilar materials with very different physical and mechanical properties which are hard to weld using conventional fusion welding processes. Tensile shear testing is used to determine the Mechanical strength of friction stir lap (FSL) welds under static loading, fracture strength (σLap) corresponding to the maximum load in a test over the sample width is widely used as the strength value. During friction stir lap welding (FSLW) of dissimilar metals with large differences in melting temperatures, a metallurgical bond is established through the formation of interfacial intermetallic compounds. However, as these intermetallic compounds are generally believed to be brittle with little ductility, they are generally considered to have detrimental effect on fracture strength. The aim of the present research is to study how the interface structure is affected by FSW parameters and how the formation of interface structure affects fracture of Al-Steel and Al-Ti FSL welds.

In today’s business scenario, organizations are focusing on sustainable growth for performance measurement in supply chain. For this purpose, sustainable flexibility is an important issue to fulfill the environmental, economic and customer’s needs, which is helpful for sustainable growth for an industry. In this paper, different factors related to sustainable flexibility in supply chain management are identified through literature review and experts’ opinions in this domain. Further, an attempt has been made to develop the interactions among these factors using Total Interpretive Structural Modeling (T-ISM) technique. This paper also employs Cross Impact Matrix Multiplication Applied to Classifications (MICMAC) based analysis to create policy to implement for sustainable growth in industries. Findings of this research give valuable decision-making insight and implications about the relative importance and the interdependence of flexibility factors in sustainable supply chain management for academicians and practicing managers in sustainable growth of an industry.