This paper aims a novel and a useful multi-objective optimization approach named Non-Dominated Sorting Ions Motion Algorithm (NSIMO) built on the search procedure of Ions Motion Algorithm (IMO). NSIMO uses selective crowding distance and non-dominated sorting method to obtain various non-domination levels and preserve diversity amongst the best set of solutions. The suggested technique is employed to various multi-objective benchmark functions having different characteristics like convex, concave, multimodal, and discontinuous Pareto fronts. The recommended method is analyzed on different engineering problems having distinct features. The results of the proposed approach are compared with other well-regarded and novel algorithms. Furthermore, we present that the projected method is easy to implement, capable of producing a nearly true Pareto front and algorithmically inexpensive.

The present work deals with some machinability studies on tool wear and surface roughness, in finish hard turning of AISI D2 steel using PCBN, Mixed ceramic and coated carbide inserts. The machining experiments are conducted based on the response surface methodology (RSM). Combined effects of three cutting parameters viz., cutting speed, cutting time and tool hardness on the two performance outputs (i.e. VB and Ra), are explored employing the analysis of variance (ANOVA).The relationship(s) between input variables and the response parameters are determined using a quadratic regression model. The results show that the tool wear was influenced principally by the cutting time and in the second level by the cutting tool hardness. On the other hand, cutting time was the dominant factor affecting workpiece surface roughness followed by cutting speed. Finally, the multiple response optimizations of tool wear and surface roughness were carried out using the desirability function approach (DFA).

This article investigates the effect of cutting parameters on the surface roughness and flank wear during machining of titanium alloy Ti-6Al-4V ELI( Extra Low Interstitial) in minimum quantity lubrication environment by using PVD TiAlN insert. Full factorial design of experiment was used for the machining 2 factors 3 levels and 2 factors 2 levels. Turning parameters studied were cutting speed (50, 65, 80 m/min), feed (0.08, 0.15, 0.2 mm/rev) and depth of cut 0.5 mm constant. The results show that 44.61 % contribution of feed and 43.57 % contribution of cutting speed on surface roughness also 53.16 % contribution of cutting tool and 26.47 % contribution of cutting speed on tool flank wear. Grey relational analysis and TOPSIS method suggest the optimum combinations of machining parameters as cutting speed: 50 m/min, feed: 0.8 mm/rev., cutting tool: PVD TiAlN, cutting fluid: Palm oil.

The purpose of this research was to recognize the influence of electricity reliability problems such as unplanned and planned outages, and load shedding on the future plans of the textile industries of Punjab (India). An opinion on the mitigation measures to diminish the impact of power outages was also obtained. The results presented here were got using the seven-point Likert item scale from the 148 respondents which were the part of a randomly selected sample of 400 textile industries from a total population of 1163 registered textile industries covering specifically the high concentration dis-tricts throughout the Punjab. Both formal and informal interview methods including dropping the questionnaire schedules at the industrial premises were employed to record the responses. A syntax for Krippendorff’s Alpha was used in SPSS to estimate the interreliability of the different sections. A non-parametric Mann-Whitney U and Friedman Q with post hoc tests were applied using SPSS for independent samples and related sample designs, respectively, in order to know the statistical significant differences among the variables and the pairs. Respondents were found highly concerned towards the power system reliability issues than the quality issues. The effect of reliability issues on the micro scale industries were found higher than the small scale industries. Based on the one hour outage duration, unplanned power outage-1 hour scenario and dangerous advance warning, planned power outage, were found highly disruptive. The growth or expansion of existing unit, like to go for costly alternative energy sources, procurement of bank loans and moving industries to other state with good energy facilities, were the four key future plans and strategies that were found highly important to the textile industries. Majority of the industries believed that almost all the future plans and decisions were dominantly impacted by the unplanned outages followed by the load shedding and planned outages. In order to diminish the impact of power outages, improved system protection and improved local protection were found the preferred outage mitigation methods.

This paper addresses the flexible manufacturing system (FMS) problems considering both machines and automated guided vehicles (AGVs), simultaneously. A new fuzzy heuristic (FH) is proposed for solving the simultaneous scheduling problem, in order to minimize the makespan by considering the available resources. For increasing the performance of FMS one of the important factors is scheduling AGV with an integral part of the machine scheduling activity. The algorithm is tested based on 82 benchmark problems and the achieved makespan are compared with other algorithms.

The aim of this study is to explore the determinants of cognitive loyalty in an online shopping envi-ronment. The study established a theoretical model by incorporating both e-service quality model and commitment-trust theory. A total of 937 responses were collected form Indian online shoppers by using the mail survey method. We assessed measurement model and structural model by using SPSS and AMOS. Study outcomes confirm that customer satisfaction, e-trust, commitment, and cognitive loyalty were strongly influenced by e-service quality and perceived value. Further, satisfaction had direct and positive influence on both e-trust and commitment but not on cognitive loyalty. E-trust had a positive impact on e-commitment and cognitive loyalty. Lastly e-commitment had a positive influence on cognitive loyalty. Based on the existing literature, there was a dearth of theo-retical understanding of cognitive loyalty in an emerging economy perspective. Thus, the current study accomplished the critical theoretical gap by encompassing previous investigations. We examined the phenomenon of customer loyalty by integrating e-service quality model and commitment-trust theory in business to consumer e-commerce environment while considering e-satisfaction as a mediator, highlighting the originality and contribution of the current research to the online consumer loyalty literature.

Image perception has been acknowledged as a critical component of branding. Perception of image is comparatively difficult for intangible entities like ‘destination’. Research initiatives, thus far, has postulated destination branding on associations namely cognitive and affective image inputs. Multi-sensory brand associations were never tested for destination branding model, although, sensory brand associations were found to play major role in the tangible product branding and influence purchase behaviours. Further, attributional elements, specific to destination are assumed to play critical role in developing the brand identity leading to choice of destination. Perceived destination brand image was empirically tested for its influence on post-travel behaviours and was identified as one of the potent travel motives, however, the predictive capability of perceived destination brand image on favourable post-travel behaviours seems to fall off due to reasons unknown. Researchers like Fournier, observed that relationship-branding can induce favourable post-purchase behaviour. This study focuses on developing a destination brand model using conventional brand associations, namely cognitive and affective image inputs, and new associations, namely, attributional and senso-ry image inputs. The study further incorporates relationship-branding as a multiplex phenomenon and tested its possible intervening impact between perceived destination brand image and post-travel behaviours. The results established the destination brand model based on the image associations and confirmed the role of relationship-branding as a para-social and socio-emotional moderator to influence post-travel visitor behaviour. The study plugs in the gap that existed in the present body of knowledge addressing destination branding and reinforces the relationship theory in establishing the ‘brand–purchase–post-purchase behaviour’ triad.

This study uses a hybrid scale to identify the factors contributing to internal and external service quality at employer-employee interface in the SMEs of emerging economies like India. 144 shop floor workers and executives working in different SMEs situated in northern India participated in an interview schedule to rate the quality of services being offered to (and delivered by) the employees in such units on 1-5 Likert scale. Application of factor analysis followed by Structural Equation Modelling developed a model showing how organization’s HR practices influences employee service quality which consequently leads to Satisfaction and Loyalty which are the established indicators of competitive advantage for such firms. The model is empirically validated using model fit indices and is found satisfactory. This paper thus proposes an empirical framework for the measurement of employee service quality in a relatively less explored sector. This study finds support for strengthening relationships with employees to achieve a culture of achievement in SMEs. The two scales proposed in this study can be used as benchmarks by SME practitioners for evaluation of services being offered to (and delivered by) their employees. The methodology used may be applied in more such settings for evolving a generic and tailor-made scale.

Nowadays, automobile industries are facing huge competition as the sector is expanding and ame-liorating day by day. All organizations are thriving to attain top position by increasing their produc-tivity. Productivity improvement is a function of eliminating rejection problem and improving system. To excel and improve the organizational efficiency a complete focus on finding root causes and eliminating factors responsible is needed. In industries, hurdles are associated with all operations. The existing study is about problem solving in a diecasting industry manufacturing alternator bracket. The authors explain the use of different statistical quality tools with the help of Minitab software to analyze root cause for enhancing the low productivity level. The streaming explanation of methodology can be useful for the organization of similar profile towards productivity improvement.

Due to various added advantages over the conventional material removal processes, non-traditional machining (NTM) processes have now been widely applied in different manufacturing industries. To achieve the desired response values, it is always recommended to operate these NTM processes at their optimal parametric settings. Various single response optimization techniques are already available to determine the optimal combinations of NTM process parameters for achieving maximum or minimum value of a single response. In this paper, a multivariate quality loss function approach is adopted for simultaneous optimization of responses for three NTM processes. It is observed that this approach outperforms the other multi-response optimization techniques, like desirability function, distance function and mean squared error methods with respect to the achieved re-sponse values. With modification of the corresponding objective function and constraints of the de-veloped non-linear programming problem, it can be effectively applied to any non-traditional as well as conventional machining process as a multi-objective optimization tool.