The objective of making an organization ‘sustainable’ needs development on the economic, environmental, and social fronts. Indian Micro, Small & Medium Enterprises are facing the competition posed by ...rising technological advances in the market. Thus, Industry 4.0 intervention shall be highly useful in this context. This study assesses the barriers involved in implementing Industry 4.0 for sustainable production, and it attempts to find causality among the barriers using the ‘Decision Making Trial and Evaluation Laboratory’ method. The study considers eight barriers to implement Industry 4.0 for sustainable production. These barriers are inter-related and have causal relationships among them. This causality is represented graphically. The applied method delineates barriers under consideration for causality into two groups, namely; ‘influencer’ and ‘influenced.’ It also illustrates the strength of the influence of one barrier over the other through numerical values. The prime contribution of this study is to not only find the influencing barriers but also to mitigate them by allocating scarce organizational resources. Mitigating the influencing barriers would help in managing the influenced challenges. ‘Technological upgradation’, ‘lack of policy frameworks’ are the top two barriers that find its place in the hierarchy of importance established by this study. These barriers are also classified into the ‘cause’ group. Also, this study establishes that ‘difficulty in access to credit’ and ‘non-readiness of the workforce’ in adopting Industry 4.0 are ‘influenced’ barriers. This study shall be of importance to the small business practitioners and government analysts in evaluating barriers in implementing sustainable production initiatives using Industry 4.0. With this, Indian Micro, Small & Medium Enterprise needs to upgrade by upskilling young working population for the forthcoming technological revolution of Industry 4.0. Finally, we suggest several important implications for managers and policymakers.
•Evaluated effects of COVID-19 on energy efficient supply chains based on trade between Turkey and China, & Turkey & the EU.•Using System Dynamics (SD), the behavior of countries against COVID-19 is ...observed.•Increase in complexity is analyzed with entropy measurement.•From the learning effect perspective, the effect on the economy and foreign trade are less than first wave of pandemic.•Perceived complexity of system decreases in second wave because of resilience of supply chain considering learning effect.
The whole world is faced with the COVID-19 epidemic that causes major disruptions in global supply chains. The aim of study is to evaluate the effects of COVID-19 on energy efficient global supply chains (SCs) and to model the global supply chain resilience and energy management affected during the COVID-19 considering trade between Turkey and China, and Turkey and the EU. In this study, firstly using System Dynamics (SD) model, the behavior of countries against COVID-19 for a certain period of time is observed, subsequently the increase in complexity is analyzed with entropy measurement to determine whether the systems are resilient or not and to mark the differences arising from reporting in the first and second wave of the pandemic in the developed model. It is determined that the second wave reporting differences is less than first wave reporting differences except Turkey. From the learning effect perspective, it has been seen that the effect on the economy and foreign trade are less than first wave of pandemic even though the number of patients originating in the second wave are higher. It means that countries responded to the second wave of COVID-19 in a more resilient way. It is found that as a major finding of this study, perceived complexity of the system decreases in the second wave because of the resilience of supply chain considering learning effect and centralized decision making ensure increasing resilience and resilience measure in global supply chains. The study is highly helpful for governments, decision makers and managers to understand and manage the impacts of COVID-19 on global supply chains being resilient and energy efficient.
Microbial fuel cell (MFC; open-air cathode) was evaluated as bio-electrochemical treatment system for distillery wastewater during bioelectricity generation. MFC was operated at three substrate ...loading conditions in fed-batch mode under acidophilic (pH 6) condition using anaerobic consortia as anodic-biocatalyst. Current visualized marked improvement with increase in substrate load without any process inhibition (2.12–2.48
mA). Apart from electricity generation, MFC documented efficient treatment of distillery wastewater and illustrated its function as an integrated wastewater treatment system by simultaneously removing multiple pollutants. Fuel cell operation yielded enhanced substrate degradation (COD, 72.84%) compared to the fermentation process (∼29.5% improvement). Interestingly due to treatment in MFC, considerable reduction in color (31.67%) of distillery wastewater was also observed as against color intensification normally observed due to re-polymerization in corresponding anaerobic process. Good reduction in total dissolved solids (TDS, 23.96%) was also noticed due to fuel cell operation, which is generally not amenable in biological treatment. The simultaneous removal of multiple pollutants observed in distillery wastewater might be attributed to the biologically catalyzed electrochemical reactions occurring in the anodic chamber of MFC mediated by anaerobic substrate metabolism.
Abstract
Magnetic fields likely play an important role in star formation, but the number of directly measured magnetic field strengths remains scarce. We observed the 38.3 and 38.5 GHz Class II ...methanol (CH
3
OH) maser lines toward the high-mass star-forming region NGC 6334 F for the Zeeman effect. The observed spectral profiles have two prominent velocity features that can be further decomposed through Gaussian component fitting. In several of these fitted Gaussian components we find significant Zeeman detections, with
zB
los
in the range from 8 to 46 Hz. If the Zeeman splitting factor
z
for the 38 GHz transitions is of the order of ∼1 Hz mG
−1
, similar to that for several other CH
3
OH maser lines, then magnetic fields in the regions traced by these masers would be in the range of 8–46 mG. Such magnetic field values in high-mass star-forming regions agree with those detected in the better-known 6.7 GHz Class II CH
3
OH maser line. Since Class II CH
3
OH masers are radiatively pumped close to the protostar and likely occur in the accretion disk or the interface between the disk and outflow regions, such fields likely have significant impact on the dynamics of these disks.
Industry 4.0 is expected to impact the decision-making and response time of organizations and shall reduce them drastically. With cyber-physical systems, internet, smart factories Industry 4.0 is ...expected to emerge as assisting tool for physical process-enabled industries towards embracing socially sustainable economic goals. The objective of this study is to identify a set of enablers of LSS so that they can assist in LSS implementation in the manufacturing organizations. A comprehensive literature survey identifies enablers of LSS with inputs from industry experts and academicians. Fourteen enablers of LSS were converged upon out of the 37 studied by the expert committee. The classical DEMAT EL method was used to derive the causal relationships between select enablers leading to CE and sustainability. An organization with an intent to implement LSS can reap benefits of achieving goals of CE and sustainability which can further be expedited with Industry 4.0.
PurposeThe study aims to map the links between Industry 4.0 (I-4.0) technologies and circular economy (CE) for sustainable operations and their role to achieving the selected number of sustainable ...development goals (SDGs).Design/methodology/approachThe study adopts a systematic literature review method to identify 76 primary studies that were published between January 2010 and December 2020. The authors synthesized the existing literature using Scopus database to investigate I-4.0 technologies and CE to select SDGs.FindingsThe findings of the study bridge the gap in the literature at the intersection between I-4.0 and sustainable operations in line with the regenerate, share, optimize, loop, virtualize and exchange (ReSOLVE) framework leading to CE practices. Further, the study also depicts the CE practices leading to the select SDGs (“SDG 6: Clean Water and Sanitation,” “SDG 7: Affordable and Clean Energy,” “SDG 9: Industry, Innovation and Infrastructure,” “SDG 12: Responsible Consumption and Production” and “SDG 13: Climate Action”). The study proposes a conceptual framework based on the linkages above, which can help organizations to realign their management practices, thereby achieving specific SDGs.Originality/valueThe originality of the study is substantiated by a unique I-4.0-sustainable operations-CE-SDGs (ISOCES) framework that integrates I-4.0 and CE for sustainable development. The framework is unique, as it is based on an in-depth and systematic review of the literature that maps the links between I-4.0, CE and sustainability.
PurposeThis paper aims to develop supply chain strategies for the fashion retail supply chain (FRSC), likely to be disrupted by the current pandemic (COVID-19) under physical and online retail ...stores. The resilient retail supply chain design is proposed under budget allocation and merchandise capacity constraints.Design/methodology/approachThis paper utilises the theory of constraint (ToC) and goal programming (GP) to address the COVID-19 impact on FRSC. The budgetary and capacity constraints are formulated with a constraint optimisation model and tested with six different priorities to deal with the physical and online stores. Next, all priorities are developed under different FRSC business scenarios. The ToC-GP-based optimisation model is validated with one of the Indian fashion retail supply chains.FindingsThe proposed optimisation model presents the optimal retailing strategies for selling fashion goods over physical and online platforms. The multiple scenarios are presented for developing trade-offs among different strategies to maximise the retailer's merchandise performance. This paper also highlighted the strategic movement from high merchandise density stores to low merchandise density stores. This implies a reduction of sales targets and aspiration levels of both online and physical fashion stores.Research limitations/implicationsThe proposed model is validated with one of the fashion retailers in India. Other nations or multiple fashion retailers might be considered for more generalisation of findings in the future.Practical implicationsThis research helps fashion retail supply chain managers deal with consumer demand uncertainty over physical and online stores in pandemic times. Limitation: Other nations or multiple fashion retailers might be considered for more generalisation of findings in the future.Originality/valueThis is the first study that considered the impact of COVID-19 on the retail fashion supply chain. The effect of physical and online platforms is mainly discussed from consumer marketing perspectives, but an inventory and resilience perspective is missing in earlier studies. The role of merchandise planning is highlighted in this study.
Textile industries are among the most polluting and demand urgent management measures to mitigate their negative environmental impact. Thus, it is imperative to incorporate the textile industry into ...the circular economy and to foster sustainable practices. This study aims to establish a comprehensive, compliant decision framework to analyse risk mitigation strategies for circular supply chain (CSC) adoption in India's textile industries. The Situations Actors Processes and Learnings Actions Performances (SAP-LAP) technique analyses the problem. However, interpreting the interacting associations between the SAP-LAP model-based variables is somewhat lacking in this procedure, which might skew the decision-making process. As a result, in this study, the SAP-LAP method is accompanied by a novel ranking technique, namely, the Interpretive Ranking Process (IRP), which reduces decision-making issues in the SAP-LAP method and aids in evaluating the model by determining the ranks of variables; furthermore, the study also offers causal relationships among the various risks and risk factors and various identified risk-mitigation actions by constructing Bayesian Networks (BN) based on conditional probabilities. The study's originality represents the findings using an instinctive and interpretative choice approach to address significant concerns in risk perception and mitigation techniques for CSC adoption in the Indian textile industries. The suggested SAP-LAP and the IRP-based model would assist firms in addressing risk mitigation techniques for CSC adoption concerns by providing a hierarchy of the various risks and mitigation strategies to cope with. The simultaneously proposed BN model will help visualise the conditional dependency of risks and factors with proposed mitigating actions.
Influence of different pretreatment methods applied on anaerobic mixed inoculum was evaluated for selectively enriching the hydrogen (H
2) producing mixed culture using dairy wastewater as substrate. ...The experimental data showed the feasibility of molecular biohydrogen generation utilizing dairy wastewater as primary carbon source through metabolic participation. However, the efficiency of H
2 evolution and substrate removal efficiency were found to be dependent on the type of pretreatment procedure adopted on the parent inoculum. Among the studied pretreatment methods, chemical pretreatment (2-bromoethane sulphonic acid sodium salt (0.2
g/l); 24
h) procedure enabled higher H
2 yield along with concurrent substrate removal efficiency. On the contrary, heat-shock pretreatment (100
°C; 1
h) procedure resulted in relatively low H
2 yield. Compared to control experiments all the adopted pretreatment methods documented higher H
2 generation efficiency. In the case of combination experiments, integration of pH (pH 3; adjusted with ortho-phosphoric acid; 24
h) and chemical pretreatment evidenced higher H
2 production. Data envelopment analysis (DEA), a frontier analysis technique model was successfully applied to enumerate the relative efficiency of different pretreatment methods studied by considered pretreatment procedures as input and cumulative H
2 production rate and substrate degradation rate as corresponding two outputs.
The ability of abundantly available heartwood of
Areca catechu to adsorb cadmium(II) ions from aqueous solution has been investigated through batch experiments at room temperature. Various sorption ...parameters such as contact time, initial concentration of cadmium(II) ion, solution pH and amount of the biomass on the adsorption capacity, were studied. The adsorbent was found to be effective for quantitative removal of cadmium(II) ions in acidic conditions and equilibrium has been achieved in 30
min at pH 6.0. The equilibrium adsorption data were fitted to Langmuir, Freundlich and Dubinin–Radushkevich adsorption isotherm models and the model parameters were evaluated. The kinetic study showed that the pseudo-second-order rate equation better described the biosorption process. The FT-IR spectrum analysis revealed that hydroxyl, carboxyl, amide and amine groups were major cadmium(II) binding groups.
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