Recent technological trends have changed how people live, consume, and interact. New emerging technologies have disrupted the way of doing business. The "digital transformation of supply chain (SC)" refers to complex organizational changes using emerging digital technologies to create new forms of revenue and business value through a customer-centric platform that captures and maximizes the utilization of real-time information emerging from various sources, enabling performance optimization and risk minimization. Companies are under common pressure to reform as new technological trends continue to emerge, but their pace of transformation is slow, especially in Indian organizations. Owing to the slow adoption rate of digital SC in India, this chapter attempts to identify the transformation factors pertinent to expanding their implementation in India. In view of this, a questionnaire- based survey has been conducted to assess the current status of the digital transformation of SC in Indian organizations and other issues related to it. Several hypotheses have also been developed and tested, which present valuable insights to organizations in digitalizing their SCs.

Purpose The aim of this paper is to study the effect of laser shock peening (LSP) on mechanical behaviour of the laser-directed energy deposition (LDED)-based printed 15-5 PH stainless steel with U and V notches. The study specifically concentrates on the evaluation of effect of scan strategy, machining and LSP processing on microstructural, texture evolution and fatigue behaviour of LDED-printed 15-5 PH steel. Design/methodology/approach For LSP treatment, 15-5 PH steel was printed using LDED process with bidirectional scanning strategy (XX [θ = 0°) and XY [θ = 90°]) at optimised laser power of 600 W with a scanning speed of 300 mm/min and a powder feed rate of 3 g/min. Furthermore, LSP treatment was conducted on the V- and U-notched fatigue specimens extracted from LDED-built samples at laser energy of 3.5 J with a pulse width of 10 ns using laser spot diameter of 3 mm. Post to the LSP treatment, the surface roughness, fatigue life assessment and microstructural evolution analysis is performed. For this, different advanced characterisation techniques are used, such as scanning electron microscopy attached with electron backscatter diffraction for microstructure and texture, X-ray diffraction for residual stress (RS) and structure information, Vicker’s hardness tester for microhardness and universal testing machine for low-cycle fatigue. Findings It is observed that both scanning strategies during the LDED printing of 15-5 PH steel and laser peening have played significant role in fatigue life. Specimens with the XY printing strategy shows higher fatigue life as compared to XX with both U- and V-notched conditions. Furthermore, machining and LSP treatment led to a significant improvement of fatigue life for both scanning strategies with U and V notches. The extent of increase in fatigue life for both XX and XY scanning strategy with V notch is found to be higher than U notch after LSP treatment, though without LSP samples with U notch have a higher fatigue life. As fabricated sample is found to have the lowest fatigue life as compared to machines and laser peened with both scan strategies. Originality/value This study presents an innovative method to improve the fatigue life of 15-5 PH stainless steel by changing the microstructure, texture and RS with the adoption of a suitable scanning strategy, machining and LSP treatment as post-processing. The combination of preferred microstructure and compressive RS in LDED-printed 15-5 PH stainless steel achieved with a synergy between microstructure and RS, which is responsible to improve the fatigue life. This can be adopted for the futuristic application of LDED-printed 15-5 PH stainless steel for different applications in aerospace and other industries. Graphical abstract

Direct Energy Deposition (DED) is a widely used method for rapid prototyping, particularly for making dense metal parts, despite its notable energy requirements. This paper presents a novel mathematical modeling method that links important process variables to energy consumption in Directed Energy Deposition (DED). The research explores the impact DED process parameters like laser power, scan speed, and powder feed rate on clad geometry and microstructure by depositing 15–5 precipitation-hardened stainless steel onto a 304L stainless steel substrate through a single-track technique experiment. The results shows the relationship between process parameters and energy use, offering guidance for improving production costs and time efficiency. Within the 200–350 W range, laser power is crucial for maintaining clad height stability, while scan speed impacts clad depth and powder feed rate influences clad width. Precise parameter management is crucial for maintaining constant clad dimensions and enhancing part quality in DED manufacturing. Four-Dimensional X-ray Microscopy (FDXM) is used to examine porosities and flaws in the deposited layer, providing insights into the melting behavior of metal powder.

Purpose Over the years, technology development has rationalized supply chain processes. The demand economy is disrupting every sector causing the supply chain to be more innovative than ever before. The digitalization of the supply chain fulfils this demand. Several technologies such as blockchain, big data analytics, 3D printing, Internet of things (IoT), artificial intelligence (AI), augmented reality (AR), etc. have been innovated in recent years, which expedite the digitalization of the supply chain. The paper aims to analyse the applicability of these technological enablers in the digital transformation of the supply chain and to present an interpretive structural modelling (ISM) model, which presents a sequence in which enablers can be implemented in a sequential manner. Design/methodology/approach This paper employed the ISM approach to propose a various levelled model for the enablers of the digital supply chain. The enablers are also classified graphically based on their driving and dependence powers using matrix multiplication cross-impact applied to classification (MICMAC) analysis. Findings The study indicates that the enablers “big data analytics”, “IoT”, “blockchain” and “AI” are the most powerful enablers for the digitalization of the supply chain and actualizing these enablers should be a topmost concern for organizations, which want to exploit new opportunities created by these technologies. Practical implications This study presents a systematic approach to adopt new technologies for performing various supply chain activities and assists the policymakers better organize their assets and execution endeavours towards digitalization of the supply chain. Originality/value This is one of the initial research studies, which has analysed the enablers for the digitalization supply chain using the ISM approach.

In the aerospace industry, regular maintenance and repair consume maximum cost and time. Direct energy deposition is an effective cutting edge repairing technology used in aircraft parts. This paper projected direct energy deposition as an important cladding technology. And as a cladding material, the acceptability of 15Cr5Ni precipitation-hardened steel is evaluated through single-layer deposition over 304 L stainless steel via direct energy deposition. 15Cr5Ni steel is a high-strength alloy mainly used for jigs, fasteners, and landing gears in the aerospace industry. Optimization of process parameters, that is, laser power, scan speed, and powder feed rate, is performed using response surface methodology through a prediction model along with a validation test. The microstructural investigation of clad cross-section and surface morphology followed by four-dimensional X-ray microscopy reveals an improved clad quality with minimized porosity and defects. A relative error of less than 5% has been found between the prediction model and experimental values, which validate the significance of optimized process parameters toward improving the clad quality for aircraft part repairing purposes.

Direct energy deposition is one of the 3D printing processes for fabricating functional parts for various engineering applications. The effectiveness of the process primarily depends on the set of process parameters and the melt pool quality. Prediction of melt pool geometry can give an edge in controlling the geometrical features of fabricated parts. In this article, a mathematical model from Toyserkani was used to predict the dimensional characteristics of the melt pool, temperature distribution, and microstructural phenomena in a laser-assisted direct energy deposition (DED) 15Cr5Ni alloy on a 304L SS substrate. The present study aims to assimilate the benefits of the Toyserkani model and inspect the effect of assumptions made on the predicted results. Predicted melt pool physical characteristics from the model and measured clad geometry from experiments were compared for the given range of process parameters (P = 200–600 W, V = 300–500 mm/min, and f = 3–5 g/min), and the graphical interpretations were made using the commercial MATLAB 9.10 software. A non-linear relation between analytical and experimental output was observed for the melt pool geometry and temperature profile within the cladding. At some critical scan speed, melt pool depth has its ultimate value, after which it decreases. Due to assumptions and thermo-mechanical property difference, the clad height value showed a deviation in the experimental and prediction model for the energy density of 104–108 J/mm2. The results from the Toyserkani model were reasonably similar to those of the experimental and could predict the melt pool characteristics with improved accuracy. The application of this study can predict the clad features analytically, thus enabling the explanation of the dependence of melt pools on process parameters.

Purpose Owing to the paucity of literature, in the specific context of mass customization (MC), that explains what factors need to be considered while selecting suppliers and what strategies need to be implemented for effective management of suppliers, this paper aims to explore the effective supplier selection and management strategies and also investigate their impact on the development of mass customization capability (MCC). Design/methodology/approach Through an extensive review of literature, a total of 18 factors for supplier selection and management have been identified. Further, using multiple regression analysis, the linkages between these factors and MCCs have been examined based on the data set from the survey of Indian manufacturing organizations. Findings The results indicate that while concentrating on the responsive and reconfiguration capability, all the five measures of supplier selection and the four measures of supplier management have shown a significant influence. However, in the case of relational capability, only two of the supplier selection strategies and three of the supplier management strategies have shown a notable impact. Practical implications The study provides help to the firms in deciding whom to select and how to manage the suppliers in the course of improving their MCCs. The study has shown the possibility that different types of MCCs might require different approaches to both the supplier selection and management. Originality/value To the best of the authors’ knowledge, this study happens to be the first of its kind that investigates the interconnectedness among the supplier selection and management strategies and MCCs.

Purpose The purpose of this research is to identify the crucial barriers to the implementation of mass customization (MC) in Indian SMEs and to investigate the interactions among them so that important managerial implications could be formulated to facilitate the implementation of MC in SMEs. Design/methodology/approach The contextual relationships and hierarchies of the barriers are established through the interpretive structural modelling (ISM) approach, and MICMAC analysis has been used to classify the barriers into different groups. Further, structural equation modelling based on partial least squares (PLS-SEM) has been applied to statistically validate the ISM model using the data collected through a questionnaire-based survey of Indian organizations. Findings A portfolio of barriers, containing 16 items, has been identified from the literature review and a series of semi-structured interviews of practitioners. The study develops a structural model by establishing relationships and imposing directions among the barriers and classifies the barriers according to their driving and dependence power to serve as a roadmap for SMEs willing to implement MC into practice. Practical implications The study highlights the critical barriers which have a significant impact on other barriers and need to be handled at priority. Also, the present research renders insights to SMEs to better prioritize their efforts and resources to overcome these barriers. Originality/value This research happens to be first in the MC literature that investigates the key barriers responsible for hindering the implementation of MC in SMEs and develops a statistically validated contextual model showing hierarchies and relationships of the barriers.

Purpose The purpose of this study is to investigate the effects of flexible manufacturing competence (FMC) and workforce management practices (WMP) in facilitating the development of mass customization capability (MCC). More specifically, this research analyzes not only the direct effects of FMC and WMP on MCC but also the moderating effect of WMP on the relationship between FMC and MCC. Design/methodology/approach Building on the resource-based view, a research framework depicting the linkages among the variables of interest has been proposed. The examination of the proposed research model and hypotheses are conducted by applying partial least squares-structural equation modelling (PLS-SEM) on a dataset of Indian manufacturing organizations. Findings The findings suggest that both FMC and WMP significantly and positively affect the development of MCC. Also, the results show that the relationship between FMC and MCC is strengthened by the implementation of WMP. Practical implications The study identifies several crucial practices for enhancement of flexible manufacturing competence and effective management of the workforce and also highlights the complementarities among them to develop superior MCC. Originality/value While the research on the antecedent of MCC has increased substantially, the understanding of the interactions among FMC, WMP, and MCC is still limited. This is the first study that sheds light on the interconnectedness among the variables of interest.

Purpose The importance of supply network flexibility (SNF) in the development of mass customization capability (MCC) has been implied in the literature but seldom subjected to empirical investigation. To fill the gap and contribute to MC literature, this paper aims to examine the role of SNF in facilitating the development of MCC of organizations. Furthermore, it has been investigated whether the use of information and communication technologies (ICTs) strengthens the above relationship. Design/methodology/approach Drawing on the supply chain literature and dynamic capability theory, the study proposes a research framework depicting the interconnectedness among the variables of interest. The proposed framework has been tested using structural equation modelling based on partial least squares by using the data collected from a questionnaire-based survey of a sample of Indian manufacturing organizations. Findings The findings indicate that the dimensions of SNF, namely, sourcing flexibility and supplier flexibility, positively affect the MCC of the organizations and the strength of these relationships is further amplified by the implementation of ICTs. Practical implications The study shows the managerial opportunities for the development of a flexible and competent supply network to facilitate the development or enhancement of MCC. Originality/value This study contributes to scant literature by providing empirical evidence for the relationship between SNF and MCC. Further, this study enriches the understanding of the crucial role of ICT by exploring its moderating effect on the relationship between the variables of interest.

In today's world of heightened competition and ever-growing demand of customers, the development of customer-centric and learning-oriented culture, mass customization capability (MCC), and effective implementation of customer relationship management (CRM) are important determinants of success, but the existing research has largely overlooked how these factors interact and affect firm performance (FP). To address the gap, the present study proposes and empirically examines a framework that relates CRM and organizational culture (OC) to MCC and FP. Based on the data collected through a questionnaire-based survey of Indian manufacturing organizations, the proposed framework and associated hypotheses are empirically examined by using structural equation modelling based on partial least squares (PLS-SEM). The results indicate that the extent of effort employed by the firms to implement CRM and development of learning-oriented OC positively affects FP. Furthermore, MCC and OC have significant indirect impact on the relationship between CRM and FP.

Purpose Digital supply chain (DSC) is an agile, customer-driven and productive way to develop different forms of returns for companies and to leverage efficient approaches with emerging techniques and data analytics. Though the advantages of digital supply chain management (DSCM) are many, its implementation is quite slow for several reasons. The purpose of this paper is to identify the major barriers which hinder the adoption of DSC and to analyse the interrelationship among them. The barriers of DSC are explored on the basis of existing literature and experts’ opinion. Design/methodology/approach This paper uses the interpretive structural modelling (ISM) approach to develop a hierarchical structural model which shows the mutual dependence among the barriers of DSC. Cross-impact matrix multiplication applied to classification analysis was performed to represent these barriers graphically on the basis of their driving power and dependence. Findings The research demonstrates that the barriers “no sense of urgency”, “lack of industry specific guidelines”, “lack of digital skills and talent” and “high implementation and running cost” are the most significant barriers to digital transformation of supply chain. This paper also suggests some managerial implications to overcome the barriers which hinder the implementation of digital transformation of supply chain. Practical implications This paper assists managers and policymakers to understand the order in which these barriers must be tackled and adopts a roadmap for successful implementation of DSCM and reap its benefits. Originality/value This is one of the initial research studies which has analysed the barriers of DSC using ISM approach.

In this research a short review of three advanced materials i.e. 18 Ni 300 Maraging steel, precipitation hardened stainless steel (PH stainless steel) and high entropy alloys (HEAs) is done that are currently being used in metal additive manufacturing along with an experimental investigation in which direct metal deposition (DMD) of precipitation hardened steel is performed to evaluate the effect of powder feed rate onto the deposited layer quality (wrt clad height, dilution and energy density). The aim is to review the high strength advanced materials which has been recently developed but yet not well investigated through additive manufacturing and to investigate the clad quality of deposited PH stainless Steel for variable powder feed rate keeping other process parameters constant.

PurposeCurrent dynamic and turbulent business environment calls for adopting newer strategies so that organizations can create a niche for itself in the market, mass customization (MC) being one of them. The purpose of this paper is to identify the critical enablers necessary to realize the objectives of MC, study the relationship among them and prioritize them in order of their importance so that a clear roadmap can be easily prepared for successful implementation of MC.Design/methodology/approachA portfolio of enablers of MC has been elicited from a thorough review of literature and experts’ opinion. Then, contextually relevant relations are chosen for each pair. In addition, a hierarchy-based structural model is developed by using Interpretive Structural Modelling (ISM) technique.FindingsThe findings classify the enablers into different groups according to their driving and dependence power. The findings show the enablers of strategic importance that need focused attention. This paper develops a structural model including hierarchy of enablers that forms a basis for the firms considering transition to MC.Practical implicationsThis paper allows the firms to differentiate the dependent and independent variables and their mutual relationships, also by identifying and establishing the connection and relationships among the enabling practices; firms can better prioritize the resources and implementation effort to successfully provide each customer exactly they want.Originality/valueThis paper happens to be one of the first of its kind in the area of mass customization research that presents a contextual model having a hierarchy of enablers.

Many global supply chains are unequipped to cope with the world we are entering. For that reason, supply chain managers need to shift their attention from cutting costs to enabling new processes, and make corporations more connected and agile to create value across the enterprise. New digital technologies that are emerging everyday are on their way to disrupt nearly all the areas of traditional business processes. The key business priority of almost every industry will find itself in the centre of this upcoming digital era. The process of digitization affects almost everything in today’s organizations, including supply chain management and puts huge pressure on organizations to change. Hence it is crucial for managers to understand the implication of digitization on their organization and employees. Current scenario emphasises on the importance of management of people and organization issues in digital transformations. The effect of digitization includes varied impacts on economy as a whole; create tremendous opportunities and challenges for businesses. In the current world of globalization digitization is not a choice but an imperative for all businesses across all industries. Manufacturing processes and work, business model, products and services are the main targets of digitization. The digital transformation enablers and framework discussed in this study-comprised of six techniques of Big data, Cloud services, Unique identification and display innovation, Robotics, Sensors and geolocation, and nanotech and 3D printing-can serve as enablers of digitization.

In the course of becoming more responsive to the turbulent market and highly diversified demands of customers and also to achieve competitive advantage, adoption of mass customization (MC) practices are inevitable. The paper explores the barriers to MC implementation in small-and-medium enterprises (SMEs) involved in furniture manufacturing business and proposes panacea for these barriers. For the above purpose, a qualitative study comprising semi-structured interviews and plant visits of SMEs are performed. The qualitative data obtained from the interviews are analyzed and a portfolio of barriers and their causes are identified, and solutions of these barriers are suggested through rigorous brainstorming. The study advocates the use of web based product configurator along with the development of network among the SMEs.

This paper attempts to highlight the environmental factors which have more dominant effect in the selection of green suppliers in GSCM (Green Supply Chain Management). Other than the qualitative and quantitative factors, risk and opportunities also need to be included in the in the wide range of factors while selecting an appropriate green supplier. A frame work has been proposed for the selection of the best supplier for a GSCM based on ANP (Analytical Network Process). The findings are that organizations should give equal importance to risk and opportunities and also qualitative and quantitative criterion. One of the findings is that Change in Customer Taste (CCT) is highly significant with all of the risk factors. This indicates that organizations should be ready for this situation and adopt such flexible system which has more potential to face it. Other findings also show the effect of various factors considered in risk and opportunities criteria. To validate the proposed model a discussion with experts of automobile companies has been carried out, to understand the factors organizations attach more significance while selecting the most appropriate supplier keeping the environmental performance in mind.

The effect of electroless metallic coating on 3D printed acrylonitrile–butadiene–styrene plastic parts surface has been studied. Owing to its excellent toughness, good-dimensional reliability, good-process capability, chemical resistance and cost-effectiveness, acrylonitrile–butadiene–styrene is used for fabrication of parts using a 3D open source printer. These parts are further metallic coated using electroless copper deposition technique. Two different surface preparation processes, namely aluminium paint paste and aluminium epoxy paste have been used for electroless coating. After the surface conditioning of parts using these methods, copper is deposited electrolessly using acidic solution, containing 12.5 wt% copper sulphate with 7.5 wt% of sulphuric acid. Deposition of copper, for two different methods, has been carried out using different temperature conditions and different time of deposition. In the first case, the temperature of the solution is initially kept at 45±2 ℃ and is allowed to come to the room temperature as the deposition is completed. In the second case, the temperature of the solution is maintained at room temperature throughout the process. Further, copper-deposited 3D printed parts were characterized based on their surface roughness measurement, electrical conductivity measurement, scanning electron microscopy, energy dispersive spectroscopy and adhesion evaluation test. It has been found that both the methods used for coating show better electrical performance and more uniform copper deposition. Adhesion between copper layers and 3D printed acrylonitrile–butadiene–styrene substrates is found to have good strength for Al-Epoxy-coated parts.

Plating is use to improve the performance of component by providing a metallic layer on to the surface of component. Plating of ABS (acrylonitrile-butadiene-styrene) parts has been studied on four different geometries parts surface. These parts are produced by rapid prototyping technique using the layer-wise deposition principles. Due to its excellent toughness, good dimensional constancy, good process capability, chemical resistance and cheapness, ABS is used for part fabrication. ABS is engineering thermoplastic composed of an elastomer namely butadiene dispersed as a grafted particulate phase in a thermoplastic matrix of styrene and acrylonitrile copolymer. These parts are further Metalize by using electroless copper deposition technique. Two distinct processes have been considered for surface preparation of parts such as aluminum carbon black paste (Al-C paste) coated ABS parts, and ABS parts prepared using chromic acid for etching. After surface conditioning of parts using these routes, Cu (copper) is deposited electrolessly using four different acidic solutions. The acidic solution has contained 5 wt% CuSO4 (copper sulphate) with 15 wt% of individual H2SO4 (sulphuric acid), HF (hydrofluoric acid), H3PO4 (phosphoric acid), and CH3COOH (acetic acid) acids for the preparation of four different acidic solution. Deposition of copper in different acidic solutions for different two routes at room temperature for 24hr and 48 hr is carried out. Further, the results are analyzed and compared based on their electrical conductivity measurement, scanning electron microscopy (SEM), and energy dispersive X-ray spectroscopy (EDS). Outcome shows that Al-C pasted samples demonstrated better electrical performance and more even Cu deposition in all acidic solutions in comparison to other route adopted for surface preparation.

In this research, an attempt has been made to find out the influence of the process parameter along with their interactions on the dimensional accuracy of part fabricated using two different rapid prototyping machines namely fused deposition modelling machine, and a low cost open source 3D printer. 3D open source printer (3D-OSP) is one of the newly developed rapid prototyping (RP) process for part fabrication. It has been observed from previous research that the contribution of parameters such as raster width, slice height, and path speed are the most significant to the dimensional accuracy of 3D open source product while raster width, slice height, and tip dimension are the most influencing factors for fused deposition modelling machine. Taguchi parameter design of experiment method has been used to find out the optimum parameters level to minimize percentage change in length (L1), length (L2) and height (H) of test specimens fabricated by each of these two rapid prototyping machines. Experimental result revels that there is different optimal parameters level setting for each dimensional characteristics namely change in length (L1), length (L2) and height (H). Therefore, grey relational method is used to obtain optimum factor level of each dimensional characteristic simultaneously. Dimensional accuracy of parts fabricated by two different technique namely 3D open source printer and fused deposition modelling machine is within a desired range. Appropriate controls of machine process parameters improve the dimensional accuracy of parts. It is concluded that a low cost 3D open source printer gave sufficient amount of part accuracy when it is compared with the industrial based fused deposition modelling machine.