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This paper aims to assist managers and food supply chain practitioners in efficiently implementing lean and green (LG) practices for sustainability. Examining barriers to LG practices, as well as prioritizing mitigation strategies in the food supply chain, are all part of this work.

Using a combination of literature review and expert team inputs, this paper investigated the LG barriers and their solutions under PESTEL (Political, Economic, Social, Technological, Environmental and Legal) framework. To prioritize them, this work used the fuzzy best worst method (fuzzy BWM) with the fuzzy technique for order preference by similarity to ideal solution (FTOPSIS).

From the fuzzy BWM, the economic barriers were identified as the most significant. From the FTOPSIS approach, top management expertise and commitment to adopting LG practices were identified as the best solution for overcoming the barriers.

This paper discusses the barriers and solutions for successfully implementing LG techniques from the real-time food supply chain. The practitioners and food chain managers welcomed the methodology for its use in prioritizing the barriers to LG practices. Conclusions drawn from this work were found to be realistic.

The original contribution of this study is to present the model framework for barriers and solutions of LG practices in the dairy supply chain using the hybrid MCDM technique.

Milling is a flexible creation process for the manufacturing of dies and aeronautical parts. While machining thin-walled parts, heat generation during machining essentially affects the accuracy. The workpiece temperature (WT), as well as the responses like material removal rate (MRR) and surface roughness (SR) for input parameters like cutting speed (CS), feed rate (F), depth-of-cut (DOC), step over (SO) and tool diameter (TD), becomes critical for sustaining the accuracy of the thin walls.

Response surface methodology was used to make 46 tests. To convert the multi-character problem into a single-character problem, the weightage was assessed using the entropy approach and the grey relational coefficient (GRC) was determined. To investigate the connection among input parameters and single-objective (GRC), a fuzzy mathematical modelling technique was used. The optimal performance of process parameters was estimated by grey relational entropy grade (GREG)-fuzzy and genetic algorithm (GA) optimization.

SR was found to be a significant process parameter, with CS, feed and DOC, respectively. Similarly, F, DOC and TD were found to be significant process parameters with MRR, respectively, and F, DOC, SO and TD were found to be significant process parameters with WT, respectively. GREG-fuzzy-GA found more suitable for minimizing the WT with the constraint s of SR and MRR and provide maximum desirability of 0.665. The projected and experimental values have a good agreement, with a standard error of 5.85%, and so the responses predicted by the suggested method are better optimized.

The GREG-fuzzy-GA is a new hybrid technique for analysing Inconel625 behaviour during machining in a 2.5D milling process.

Food supply chains (FSCs) are fast becoming more and more complex. Sustainability is a necessary strategy in FSCs to meet the environmental, economic and societal requirements. Industry 4.0 (I4.0) applications for a circular economy (CE) will play a significant role in sustainable food supply chains (SFSCs). I4.0 applications can be used in for traceability, tracking, inspection and quality monitoring, environmental monitoring, precision agriculture, farm input optimization, process automation, etc. to improve circularity and sustainability of FSCs. However, the factors integrating I4.0 and CE adoption in SFSC are not yet very well understood. Furthermore, despite such high potential I4.0 adoption is also met with several barriers. The present study identifies and analyzes twelve barriers for the adoption of I4.0 in SFSC from an CE context.

A cause-effect analysis and prominence ranking of the barriers are done using Rough-DEMATEL technique. DEMATEL is a widely used technique that is applied for a structured analysis of a complex problems. The rough variant of DEMATEL helps include the uncertainty and vagueness of decision maker related to the I4.0 technologies.

“Technological immaturity,” “High investment,” “Lack of awareness and customer acceptance” and “technological limitations and lack of eco-innovation” are identified as the most prominent barriers for adoption of I4.0 in SFSC.

Successful mitigation of these barriers will improve the sustainability of FSCs through accelerated adoption of I4.0 solutions. The findings of the study will help managers, practitioners and planners to understand and successfully mitigate these barriers.

Additive manufacturing (AM) is expected to significantly transform the operations in manufacturing sector. It is also proposed to have optimistic applications in the medical supply chains (SC). However, its adoption in medical sector is faced with a range of barriers. Motivated by the need to establish an AM-based medical SC in a developing economy, the present paper analyses the potential barriers that would hinder the adoption of AM in medical SC.

Based on an extensive literature review and expert discussions, 12 significant barriers have been identified, which are analysed using an integrated interpretive structural modelling–analytical network process (ISM–ANP) methodology. An interrelationship between these barriers using ISM has been analysed to determine the driving-dependence power of these barriers using MICMAC (Matrice d' Impacts Croises-Multiplication Applique' e a' Classement) analysis. The barriers are then ranked using the ANP approach.

It has been focussed that the non-availability of a variety of materials, lack of education and training to designers and workers and production technology limitation are the most critical barriers. The results suggest that the managers should give greater significance to the technological and organizational barriers.

An approach to overcome these barriers can help the managers and organizations to develop successful AM-based SCs. The study is the first to identify and analyse the barriers for successful adoption of AM in medical SC context.

An integrated intuitionistic fuzzy (IF) modelling-based framework for examining the performance analysis of a packaging unit (PU) in three different stages has been proposed.

For the series and parallel configuration of PU, a mathematical model based on the intuitionistic fuzzy Lambda–Tau (IFLT) approach was developed in order to calculate various reliability parameters at various spreads. For determining membership and non-membership function-based reliability parameters for the top event, AND/OR gate transitions expression was employed.

For 15%–30% spread, unit’s availability for the membership function falls by 0.006442%, and it falls even more by 0.014907% with an increase in spread from 30% to 45%. In contrast, for 15%–30% spread, the availability of non-membership function-based systems reduces by 0.007491% and further diminishes. Risk analysis has presented applying an emerging approach called intuitionistic fuzzy failure mode and effect analysis (IFFMEA). For each of the stated failure causes, the output values of the intuitionistic fuzzy hybrid weighted Euclidean distance (IFHWED)-based IFFMEA have been tabulated. Failure causes like HP1, MT6, FB9, EL16, DR23, GR27, categorized under subsystems, namely hopper, motor, fluidized bed dryer, distributor, grader and bin, respectively, with corresponding IFFMEA output scores 1.0975, 1.0190, 0.8543, 1.0228, 0.9026, 1.0021, were the most critical one to contribute in the system’s failure.

The limitation of the proposed framework lies in the fact that the results obtained for both reliability and risk aspects mainly depend on the correctness of raw data provided by the experts. Also, an approximate model of PU is obtained from plant experts to carry performance analysis, and hence more attention is required in constructing the model. Under IFLT, reliability parameters of PU have been calculated at various spreads to study and analyse the failure behaviour of the unit for both membership and non-membership function in the IFS of [0.6,0.8]. For both membership- and non-membership-based results, availability of the considered system shows decreasing trend. To improve the performance of the considered system, risk assessment was carried using IFFMEA technique, ranking all the critical failure causes against IFHWED score value, on which more attention should be paid so as to avoid sudden failure of unit.

The livelihood of millions of farmers and workers depends on sugar industries. So perpetual running of these industries is very important from this viewpoint. On the basis of findings of reliability parameters, the maintenance manager could frame a correct maintenance policy for long-run availability of the sugar mills. This long-run availability will generate revenue, which, in turn, will ensure the livelihood of the farmers.

Mathematical modelling of the considered unit has been done applying basic expressions of AND/OR gate. IFTOPSIS approach has been implemented for ranking result comparison obtained under IFFMEA approach. Eventually, sensitivity analysis was also presented to demonstrate the stability of ranking of failure causes of PU.

The purpose of this paper to present a practical and systematic approach to estimate the availability of a process plant using generalized stochastic Petri nets (GSPNs). The actual live problem at a fluid catalytic cracking unit (FCCU) of a refinery is used to demonstrate this approach.

A majority of models used for estimation of availability of a complex system are based on the assumptions that the failure of the system is associated with only a few states, and the system does not face different operating conditions, repair actions and common-cause failures. In reality, this is often not the case. Therefore, it is necessary to construct more sophisticated models without such assumptions. In this paper, an attempt has been made to model interaction of component failures, partial failures of components and common-cause failures.

The superiority of this approach over other modeling approaches such as fault tree and Markov analysis is demonstrated. The proposed GSPN is a promising tool that can be conveniently used to model and analyze any complex systems.

GSPN was used to model the reactor-regenerator section of FCCU, which is quite a large system, which shows the strength of modeling capability. The use of Petri nets (PNs) for modeling complex systems for the purpose of availability assessment is demonstrated in this paper. Sensitivity analysis was also carried out for various subsystem/components.

No similar work has been conducted for FCCU using GSPN as per literature incorporating different operating conditions and common-cause failures. The understanding and usage of PNs require a steep learning curve for the practitioners, and this paper provides an approach to estimate availability measures for the complex system.

The purpose of this paper is to investigate the optimized setting of wire-cut electrical discharge machining (WEDM) parameters at which material removal rate (MRR) and mean roughness depth (Rz) set a compromise. The problem in the processing of Ti-6Al-4V by conventional processes is a high strength, high hardness, high tool wear. Due to which WEDM is adopted to machine Ti-6Al-4V biomedical alloy. Ti-6Al-4V alloy has a number of applications in the engineering and medical industries due to its high strength biocompatibility.

The effect of control factors (i.e. pulse on-time: Pon; pulse off-time: Poff; servo voltage: SV) on the MRR and Rz is investigated in the present research. The planning of experiments is done using a Taguchi-based L9 orthogonal array. The percentage influence of each factor on responses is also evaluated. The multi-objective optimization is done using the grey approach initially. After that, the results were also calculated using harmony search (HS). Therefore, a hybrid approach of grey and HS is used to find the optimized values of MRR and Rz.

The maximum value of grade calculated by grey-HS is 0.7879, while in the case of the experimental run the maximum value of grey grade is 0.7239. The optimized setting after improvisation at this grade value is Pon: 130 µs; Poff: 45 µs and SV: 70 V for MRR and Rz collectively. The validation of the suggested setting is completed by experimentation. The values of MRR and Rz are coming out to be 6.4 mm³/min and 13.84 µm, which represents improvised results after the implementation of the HS algorithm.

The integration of the grey approach with the HS principle in the manufacturing domain is yet to be explored. Therefore, in the present research hybrid approach of grey-HS is implemented in the manufacturing domain having applications in medical industries.

The purpose in this paper is to develop a systematic literature review aiming to reveal innovation opportunities associated with the thematic collaboration and trust in the reverse logistics field.

The authors adopted a parallel analysis approach segregating the systematic literature review papers in two groups at NVivo®, collaboration and trust in the supply chain and collaboration and trust in reverse logistics, aiming to explore in the first group of papers insights for innovation on collaboration and trust in reverse logistics. The content analysis strategy was supported by the knowledge exchange theory described in Gravier et al. (2008).

Reverse logistics is hardly dissociated from broader sustainable supply chain management approaches, which make all considerations on collaboration and trust designed for such approaches valuable and valid for reverse logistics. Collaboration and trust concepts in supply chain and in reverse logistics contexts are quite similar, while collaboration/trust is mandatory for managing networks in sustainable approaches and in reverse logistics, as well. Downstream and upstream, the chain disruptive innovation business models may be developed between focal companies and returns system third-party logistics providers, fourth-party logistics providers or end-customers, in a business-to-customer collaboration approach. Several collaboration technologies are listed in three perspectives: knowledge sharing, knowledge generation and knowledge implementation.

This study uses a specific protocol for the systematic literature review, and due to inclusion and exclusion criteria, other protocols can provide different results. The strategy of analysis under the knowledge exchange perspective may give a type of result different from other perspectives.

This research systematizes the existing knowledge on the collaborations and trust, which is a priority basis for reverse logistics, providing insights to researchers and practitioners in the area and identifying an agenda for future studies.

This study seeks to understand how business group-affiliated firms perform in emerging markets. Previous studies identify that in spite of changes in the competitive landscape, seemingly counter-intuitively, business group affiliates outperform their standalone counterparts in emerging markets. This study adopts a knowledge-based view to resolve this apparent paradox.

This study uses a problematization methodology to qualitatively analyze the strategic decisions of Indian business group-affiliated firms. This study cross-validates their analysis with the empirical results available in published academic and practitioner articles.

Previous studies explain this outperformance paradox based on assumptions that include filling institutional voids, access to strategic resources and leveraging political connections. By questioning these assumptions, this study identifies an alternative explanation that is based on affiliates’ ability to adopt a strategic approach that balances knowledge capital acquired through international expansion and innovation.

The findings have important implications for managers of business group-affiliated firms in emerging markets, as well as for those in developed markets seeking to compete or collaborate in emerging markets.

This study provides a framework for managers of business group affiliates to identify suitable pathways to higher levels of competitive advantage.

The purpose of this paper is to prepare a methodology to evaluate availability analysis of distillery plant using Petri nets (PN). The effect of various failures, repair rate and availability of repair facilities on the system has been studied.

The PN model of a system is developed to study the dynamic behavior of the system under various working conditions. Availability analysis of the plant is presented taking into consideration of failure and repair rates of their subsystems and has been carried out using Monte Carlo simulation.

The bottle washing machine is the most critical machine from a maintenance point of view which has more compact on the system performance as compared to other machines. The availability analysis of distillery plant helps the management to adopt a suitable maintenance policy to improve upon plant production and plant availability.

The application of this proposed PN-based approach is very useful in finding the most critical subsystem and its effect on the performance of the system in terms of availability and plant production. Further, the advantage of the PN approach is that dynamic behavior of the system under consideration is modeled with graphic representation of the system and given distribution can be associated with the subsystems for analysis. The superiority of this approach over others, such as network, fault tree and Markov analysis, is outlined in the paper.