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Agile manufacturing (AM) has the new scenario in the business system and it is widely seen as a “New Revolution” in the manufacturing firms. AM, which continuously focusses on the adoption of new methodologies and quickly respond to the customer expectation. For this reason, many of the research studies are focussed on the AM environment and this system is mainly followed in large sector only and most of the small- and medium-sized enterprises (SMEs) are not aware of it. Especially in the developing countries which are still lagging behind in the implementation of AM. Considering the above reason, the purpose of this paper is to assess the awareness of AM in Indian SMEs.

By means of researching many literature reviews and empirical data collected by using a self-administrated instrument distributed to the selected Indian SMEs and the awareness about the AM was investigated. The authors have selected 100 SMEs in Indian service sectors and sent the data sheets through by e-mail and also by directly visiting the company and collected the information. A total of 68 useable survey data’s were identified from the final analysis. The study data sample consists of a group of selected Indian SMEs, from different industries including the pump and foundry industries. The collected data were analyzed using the graphical representation method and by the statistical analysis.

The analysis revealed the significance and usage of AM in the Indian SMEs. The results also suggested that the Indian SMEs are well aware of the AM system, through more efforts need to be focussed on implementing this system properly and effectively to improve these standards. By the use of agile models and frameworks in small and medium sized enterprises (SMEs), would result in cost-effectiveness in their quality and services and can be continuously improving the ongoing agile practices.

Indian SMEs managers seem to be stronger familiar with the agile concepts and practices and they believe that agile environment would guaranteeing in their services and high-quality products. Therefore, SMEs should concentrate and invest in agile practices that would help them to improve their competitiveness in the global market. Further, Indian SMEs managers and practitioners would concentrate more about this maintenance of standards and with this dynamic approach it takes toward the agile environment to meet the future challenges.

The data collected and the results provided in this paper will help in understanding, the awareness about the AM environment in Indian SMEs. Also, suggest some additional improvements in the knowledge of agile to the managers and practitioners in the Indian SMEs, which could enhance the level of agile implementation.

The assessment of agile awareness in Indian SMEs, along with the concepts of understanding the AM environment, has been explained in the literature on AM in the Indian SMEs.

The purpose of this paper is to develop hybrid aluminum metal matrix composite by stir casting process, reinforced with graphite and hard boron carbide particles to enhance the wear resistance. An attempt is made to optimize the wear (weight loss) and coefficient of friction (COF) by considering three factors, i.e. normal load, track diameter and sliding speed which were varied at three different levels.

The effect of graphite and boron carbide on microhardness was studied by adding them in varying percentages. After determining the best combination of hybrid reinforcements, optimization of wear (weight loss) and COF was carried out at various levels of considered factors. Taguchi design of experiments was used using the software “Minitab 16.1”. ANOVA was used to analyze the effect of various parameters on wear and COF. To validate the results, mathematical modeling was carried out in terms of regression equations and results obtained by regression equations.

The results revealed that the lower weight percentage of graphite (3 per cent) and boron carbide (1 per cent) significantly improved microhardness of developed composites. Results of ANOVA revealed that normal load was the main contributing factor for wear and COF. The results obtained by regression equations and confirmatory tests were within the results obtained by ANOVA.

To the best of the author’s knowledge, very less work has been reported on optimization of wear and COF using hybrid reinforcement particles of graphite and boron carbide.

Compression ignition engines are being used in transportation, agricultural and industrial sectors due to its durability, fuel economy and higher efficiency. This paper aims to present investigation focuses on the utilization of nano additives in emulsified blends of Pongamia biodiesel and its impact on combustion, emission and performance characteristics of a diesel engine.

Pongamia biodiesel was produced through two-stage transesterification process. Taguchi method with L₉ Design of experiment was adopted to study the stability of fuel blends and 75 per cent diesel, 20 per cent biodiesel, 5 per cent water and 6 per cent of surfactant was found to be stable. Further, aluminum oxide nanoparticle was blended into the emulsified fuel in mass fraction of 100 ppm (D75-BD20-W5-S6-AO100) through ultrasonicating technique.

Oleic acid was found to be in prominent proportion in the Pongamia biodiesel. It was observed that D75-BD20-W5-S6 and D75-BD20-W5-S6-AO100 had the ability to produce lower in-cylinder pressure and rate of heat release compared to D100, B100 and D75-BD20 fuel blends. However, a higher rate of pressure rise was noticed in D75-BD20-W5-S6 and D75-BD20-W5-S6-AO100. Lower brake specific fuel consumption and relatively higher brake thermal efficiency were noticed in D75-BD20-W5-S6 and D75-BD20-W5-S6-AO100. Moreover, lower NO_x and smoke emission were also observed for nano-emulsified fuel blends.

Metal-based nano-additive significantly improved the physio-chemical properties of the fuel. Based on the literature, it is understood that emulsified biodiesel blend with nano enrichment using Pongamia biodiesel as base fuel was not carried out. Identifying a stable blend of diesel-biodiesel-water-nano additive using Taguchi’s design of experiments approach was an added value in formulating the test fuels. Furthermore, the formulated test fuel was compared with mineral diesel, biodiesel, and diesel-biodiesel blend to understand its suitability to use as a fuel in compression ignition (CI) engine.

Objects fabricated using additive manufacturing (AM) technologies often suffer from dimensional accuracy issues and other part-specific problems. This study aims to present a framework for estimating the printability of a computer-aided design (CAD) model that expresses the probability that the model is fabricated correctly via an AM technology for a specific application.

This study predicts the dimensional deviations of the manufactured object per vertex and per part using a machine learning approach. The input to the error prediction artificial neural network (ANN) is per vertex information extracted from the mesh of the model to be manufactured. The output of the ANN is the estimated average per vertex error for the fabricated object. This error is then used along with other global and per part information in a framework for estimating the printability of the model, that is, the probability of being fabricated correctly on a certain AM technology, for a specific application domain.

A thorough experimental evaluation was conducted on binder jetting technology for both the error prediction approach and the printability estimation framework.

This study presents a method for predicting dimensional errors with high accuracy and a completely novel approach for estimating the probability of a CAD model to be fabricated without significant failures or errors that make it inappropriate for a specific application.

Pahang beaches draw more than thousand visitors throughout the year. From the year 2006 to 2018, more than 30 drowning and near-drowning cases were recorded mainly from rip currents. Rip currents are defined as unexpected currents that carried beachgoers away to seaward direction more than approximately 50 m from shore. The prediction of rip current development is very important for the protection of human life. This study aims to conduct preliminary survey and field works to identify rip current hazards.

The output would be an early warning preventative mitigation to public in Pahang. Beach state model, dimensionless fall velocity, littoral environment observation and relative tidal range were recorded for five recreational beaches during two different months (March and April 2018). The morphodynamic parameters such sediment fall velocity, sediment grain size and beach slope are then analysed using software PROFILER. Classification of risks was done based on beach morphodynamic model. The morphodynamics are classified as low tide bar rip, barred and low tide terrace associated with rip current, bar dissipative, reflective, non-bar dissipative, low tide terrace and ultra-dissipative.

Result shows three out of five recreational beaches may develop high-risk rip currents. During the first month of the survey, Batu Hitam (BH) was recorded the only one recreational beach that may develop high-risk rip current followed by Teluk Cempedak (TC) and Kempadang (KEM) as middle-risk rip current beaches, while Balok (BA) and Sepat (SEP) as low-risk rip current beaches. Different during second month of the survey, BA, BH and SEP were recorded as high-risk rip current beaches while TC and KEM as low-risk rip current beaches.

The results are consistent with beach incidents (drowning and near-drowning) reported.

The purpose of this paper is to present the analysis of barriers affecting the adoption of lean concepts to electrical and electronics component manufacturing.

Lean concepts are being increasingly applied by electrical and electronics component manufacturers to enhance product value through streamlined process. To facilitate smooth adoption of lean concepts, barriers need to be analyzed and prioritized. In this context, a structural model of 24 barriers is developed through total interpretive structural modeling (TISM) approach.

‘Changing governmental policies,’ ‘poor selection of change agents and improvement teams,’ ‘lack of top management commitment understanding and support of the system,’ ‘lack of team autonomy,’ ‘lack of flexibility and versatility’ and ‘lack of customer focus/involvement’ are found to be the dominant barriers based on TISM study. Interpretation statements are being derived from TISM model. Cross-impact matrix multiplication applied to classification analysis is conducted.

In the present paper, 24 barriers are considered. In future, additional barriers could be considered to deal with managerial advancements.

The paper reports the practical case of analysis of barriers to lean adoption in electronics component manufacture. Hence, the inferences have practical relevance.

The development of structural model for the analysis of barriers to lean implementation in electronics component manufacturing small- and medium-sized enterprises is the original contribution of the authors.