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This paper aims to focus on the application of multi-attribute decision-making methods (MADMs) to ascertain the optimal machining parameters while turning Ti-6Al-4V alloy under minimum quantity lubrication (MQL) conditions using Jatropha-curcas oil (JCO) bio-based lubricant.

The experiments were designed and performed using Taguchi L27 design of experiments methodology. A total of 27 experiments were performed under MQL conditions using textured carbide cutting tools on which different MADMs like Analytic hierarchy process (AHP), Technique for order preference by similarity to ideal solution (TOPSIS) and Simple additive weighting (SAW) were implemented in an empirical manner to extract optimize machining parameters for turning of Ti-6Al-4V alloy under set of constrained conditions.

The results evaluated through MADMs exhibit the optimized set of machining parameters (cutting speed V_c = 80 m/min, feed rate f = 0.05 mm/rev. and depth of cut a_p = 0.10 mm) for minimizing the average surface roughness (Ra), maximum flank wear (Vbmax), tangential cutting force (Fc) and cutting temperature (T). Further, analysis of variance (ANOVA) and traditional desirability function approach was applied and results of TOPSIS and SAW methods having optimal setting of parameters were compared as well as confirmation experiments were conducted to verify the results. A SEM analysis at lowest and highest cutting speeds was performed to investigate the tool wear patterns. At the highest speed, large cutting temperature generated, thereby resulted in chipping as well as notching and fracturing of the textured insert.

The research paper attempted in exploring the optimized machining parameters during turning of difficult-to-cut titanium alloy (Ti-6AL-4V) with textured carbide cutting tool under MQL environment through combined approach of MADMs techniques. Ti-6Al-4V alloy has been extensively used in important aerospace components like fuselage, hydraulic tubing, bulk head, wing spar, landing gear, as well as bio-medical applications.

The purpose of this paper is to deal with the springback problems of channel cross-section bars of linear and non-linear work-hardening materials under torsional loading. Using the deformation theory of plasticity, a numerical scheme based on the finite difference approximation has been proposed. The growth of the elastic-plastic boundary and the resulting stresses while loading, and the springback and the residual stresses after unloading are calculated.

The numerical method which has been described in this paper for obtaining the solution of elasto-plastic solution can also be used for other sections. The only care that needs to be taken is to decrease the mesh size near points of stress concentration. The advantage of this technique is that it automatically takes care of all plastic zones developing over the section at different loads and gives a solution satisfying the elastic and plastic torsion equations in their respective regions.

As expected, elastic recovery is found to be more with decreasing values of n and λ. The difference in springback becomes more and more with increasing values of angle of twist. The material will approach an elastic ideally plastic behavior with increasing values of λ and n.

It seems that no attempt has been made to study residual stresses in elasto-plastic torsion of a work-hardening material for a channel cross-section.

Delivering premium services and quality products are critical strategies for success in manufacturing. Continuous improvement (CI), as an underlying foundation for quality management, is an ongoing effort allowing manufacturing companies to see beyond the present to create a bright future. We propose a novel integrated fuzzy framework for analyzing the barriers to the implementation of CI in manufacturing companies.

We use the fuzzy failure mode and effect analysis (FMEA) and a fuzzy Shannon's entropy to identify and weigh the most significant barriers. We then use fuzzy multi-objective optimization based on ratio analysis (MOORA), the fuzzy technique for order of preference by similarity to ideal solution (TOPSIS) and fuzzy simple additive weighting (SAW) methods for prioritizing and ranking the barriers with each method. Finally, we aggregate these results with Copeland's method and extract the main CI implementation barriers in manufacturing.

We show “low cooperation and integration of the team in CI activities” is the most important barrier in CI implementation. Other important barriers are “limited management support in CI activities,” “low employee involvement in CI activities,” “weak communication system in the organization,” and “lack of knowledge in the organization to implement CI projects.”

We initially identify the barriers to the implementation of CI through rigorous literature review and then apply a unique integrated fuzzy approach to identify the most important barriers based on the opinions of industry experts and academics.

Manufacturing industries are facing dynamic challenges in today’s highly competitive world. In the recent past, integrating Industry 4.0 with the lean six sigma improvement methodologies has emerged as a popular approach for organizational excellence. The research aims to explore and analyze critical success factors of lean six sigma integrated Industry 4.0 (LSSI).

This research study explores and analyzes the critical success factors (CSFs) of LSSI. A three-phase study framework is employed. At first, the CSFs are identified through an extensive literature review and validated through experts’ feedback. Then, in the second phase, the initial list of CSFs is finalized using the fuzzy DELPHI technique. In the third phase, the cause-effect relationship among CFSs is established using the fuzzy DEMATEL technique.

A dyadic relationship among cause-and-effect category CSFs is established. Under the cause category, top management commitment toward integrating LSSI, systematic methodology for LSSI and organizational culture for adopting changes while adopting LSSI are found to be topmost CSFs. Also, under the effect category, organizational readiness toward LSSI and adaptability and agility are found to be the uppermost CSFs.

The study offers a framework to understand the significant CSFs for LSSI implementation. Insights from the study will help industry managers and practitioners to implement LSSI and achieve organizational excellence.

To the best of the authors’ knowledge, CSFs of LSSI are not much explored in the past by researchers. Findings will be of great value for professionals in developing long-term operations strategies.

The thermoplastic polymers do not decompose easily due to the presence of long-chain stable polymeric structure, and thus, causes serious effects on the environment. Recycling of these polymer wastes becomes the only solution to minimize their adverse effects on the environment. The purpose of this study was to explore the feasibility of using recycled thermoplastic material as filament for fused deposition modeling technique.

In this study, the researchers fabricated fused filaments (in-house) for fused deposition modeling (FDM) technique of additive manufacturing from secondary recycled acrylonitrile butadiene styrene (ABS) by using a twin-screw extruder. After measuring the melt flow index of the secondary recycled ABS, the twin-screw extrusion parameters (rpm/speed of the screw, extrusion temperature and load) were varied to predict their influence on the various properties (rheological/mechanical/thermal) of the fabricated filaments. Experimental work was executed as per Taguchi’s L9 orthogonal array.

Thermal analysis performed to estimate the heat carrying capacity of recycled ABS highlighted that the heat capacity of ABS increases significantly from 0.28 J/g to 3.94 J/g during the heating cycle. The maximum value of peak strength and percentage break elongation for the fused filaments was investigated at 12.5 kg load, 2,250 C extrusion temperature and 70 rpm speed.

The filaments fabricated by recycling the polymeric waste has been successfully used in the FDM machine for the preparation of the three-dimensional printed tensile specimen.

This research proposes a text analytics–based framework that examines the utility of online customer reviews in evaluating automobile manufacturers and discovering their consumer-perceived weaknesses.

The proposed framework integrates aspect-level sentiment analysis with the house of quality (HoQ), TOPSIS, Pareto chart and fishbone diagram. While sentiment analysis mines and quantifies review-embedded consumer opinions on various automobile attributes, the integrated HoQ-TOPSIS analyzes the quantified opinions and evaluates the manufacturers. The Pareto charts assist in discovering consumer-perceived weaknesses of the underperforming manufacturers. Finally, the fishbone diagram visually represents the results in the form with which the manufacturing community is acquainted.

The proposed framework is tested on a review data set collected from CarWale, a well-known car portal in India. Selecting five manufacturers from the mid-size car segment, the authors identified the worst-performing one and discovered its weak attributes.

The proposed framework can help the manufacturers in evaluating competitor; identifying consumers' contemporary interests; discovering own and their competitors' weak attributes; assessing the suppliers and sending early warnings; detecting the hazardous defects. It can assist the component suppliers in devising process improvement strategies; improving their customer network; comparing them with competitors. It can support the customers in identifying the best available alternative.

The proposed framework is first of its kind to integrate the sentiment analysis with (1) HoQ-TOPSIS to assess the manufacturers; (2) Pareto chart to discover their weaknesses; (3) fishbone diagram to visually represent the results.

The purpose of this research is to conduct a literature review on the evolution, antecedents, and outcomes of luxury consumption (LC). To accomplish our goal, we used a combination of bibliometrics and systematic approaches to review 165 articles published between 1998 and 2019. The investigation revealed that the evolution of LC is mostly driven by consumer motivation and is influenced by cultural and psychological variables. Furthermore, we explored the aforementioned antecedents of LC along four major axes. Antecedents related to (1) individual characteristics, (2) brand components, (3) cultural and social values, and (4) organizational strategies. Furthermore, based on the outcomes of LC, we found two categories (individual traits and social values). The chapter concludes by proposing a broader research agenda for the future.