Heavy Manufacturing Industry Research Articles

The green trade benefits and horizontal ecological compensation from the perspective of embodied carbon emissions: A case study of the Yellow River Basin, China

The horizontal ecological compensation plays an important role in balancing the interests of all parties and coordinating regional development in the basin. However, the mechanism of ecological compensation based on embodied carbon emissions is still poorly understood. Here, taking the Yellow River Basin as the research area, we use the multi-regional input-output (MRIO) model to measure the embodied carbon transfers between its seven urban agglomerations in 2012 and 2017 from the viewpoint of value-added trade benefits. Further, for the first time, the green trade benefits and ecological compensation amounts are analyzed. The results indicate that: (1) The transfer of trade-embodied carbon among the urban agglomerations in the basin showed obvious spatial heterogeneity and geographic proximity effects, and trade-embodied carbon outflows (inflows) had a pattern of "highest in the midstream, second in the downstream, and lowest in the upstream". (2) The industry composition of the urban agglomerations in relation to embodied carbon outflows (inflows) was similar, mainly in the service and heavy manufacturing industries. (3) The spatial pattern of green trade benefits in the basin had shifted from "high in the north and low in the surrounding area" to "high in the east-central part and low in the west". (4) The pattern of ecological compensation in the basin had shifted from the upstream surplus, the middle and downstream deficit to the midstream deficit, and the upstream and downstream surplus. Therefore, we recommend improving energy structures in high-demand urban agglomerations by adopting clean energy, focusing on decarbonization and energy efficiency in resource-rich regions. Additionally, promoting low-carbon economies, especially in the service and heavy manufacturing industries, implementing differentiated emission reduction strategies, and optimizing carbon compensation mechanisms considering regional disparities and resource endowments are crucial. It is expected that the study can enrich the scientific basis of horizontal ecological compensation and increase the fairness of regional carbon emission rights allocation.

Lessons from Germany for levelling up in the UK

This paper suggests how lessons from Germany’s national-level, comprehensively focused place-based regeneration (or levelling up) efforts could be applied in the UK. It draws the direct linkage between spatial inequality and the decline of large-scale heavy manufacturing industry at the end of the 20th century in Germany and the UK. It also posits that rapid deindustrialisation, poor-quality education and other indices of poverty and economic inequality have fuelled political fragmentation — including loss of public trust in government, national and civic institutions — in both countries. The paper explores and compares two sets of German redevelopment efforts over time, in the industrial heartland of the former West German Ruhr region and across the former East Germany, to assess their impacts on reducing political polarisation as well as bolstering redevelopment. It highlights which elements of these efforts have been most successful and why. The German experience, as described in the paper, clearly demonstrates that it takes decades to achieve measurable positive economic outcomes from redevelopment programmes. Political outcomes can also be mixed, even negative, if grassroots sentiment and public well-being are ignored or discounted in the process. In the former East Germany, despite huge transfers of development funds, grievances rooted in the economic and political dislocation of German unification in the 1990s have fuelled anti-establishment politics. The paper also examines how grassroots, philanthropic and private sector actors work alongside regional and federal governments in Germany in shaping positive political as well as socio-economic outcomes and how this might be most effectively adapted for the UK.

Empirical Modeling and Analysis of Process Parameters in Laser Beam Cutting Process

The research has been originated based on the persuasive applications of Lasers in the field of various engineering industries, i.e., Aerospace, Automobile, Electronic and Heavy manufacturing industries to machine a variety of metals and alloys. Out of all the machining processes available, Laser Beam Machining is considered to be the best one, because of the following advantages, i.e., quick material removal, non-contact, non-wearing tool, involves highly localized heat input to the work piece, reduces distortion, and offers no tool wear, diminishes tendency of cracking. The present paper focused mainly on developing the empirical relationships between the input process parameters and the output responses in Laser beam cutting process. Laser power, Cutting Speed, Gas pressure and Focal distance are the input process parameters. The output responses considered are related to the quality of cut. Surface roughness is the first output responses considered and the second one is Burr height. Total number of experiments carried out is 27 based on the Taguchi Design of Experiments. Haste alloy C276 is the work material. Response Surface Methodology is applied for the Experimental data of 31 samples to derive the empirical relationships. Later ANOVA analysis is also carried out to check the adequacy of the derived equations. Based on the ANOVA analysis, the models are classified as significant or not significant. Further the significant models can be used for optimizing the Laser beam cutting process. Once the process is optimized, it can be automated, so that the process can be run very efficiently and economically.

Intermediate Goods–Skill Complementarity

Abstract Recent research has begun to imply intermediate goods–skill complementarity; however, this possible complementarity has been hypothesized but not statistically tested, despite the increasing importance of intermediate goods in production. This study provides statistical evidence regarding whether intermediate goods are more complementary with skilled labor than with unskilled labor. Using panel data from 40 countries over the period 1995–2009, we estimate a two-level constant elasticity of substitution (CES) production function. Our major findings are fivefold. First, at the aggregated one-sector level, the elasticity of substitution between intermediate goods and unskilled labor is 1.22, which is significantly greater than that between intermediate goods and skilled labor of 1.05, indicating intermediate goods–skill complementarity. Second, at the disaggregated level, such complementarity is primarily observed in heavy manufacturing industries and the service sector, whereas complementarity is observed between intermediate goods and unskilled labor in the primary sector and light manufacturing industries. Third, the normalization of the data and the cumulant estimators exhibit stronger results. Fourth, our baseline results are confirmed applying several robustness checks, such as switching skilled and unskilled labor or considering capital–skill complementarity. Finally, intermediate goods–skill complementarity tends to be higher for industries that use more imported intermediate goods.

The Influence of Environmental Regulation on The Innovation of Heavily Polluting Enterprises

This paper selects the listed companies of heavy pollution manufacturing industry in SSE and Shenzhen Stock Exchange from 2014 to 2018 as samples, and establishes A step-by-step regression model to explore the relationship between environmental regulations, financing constraints and enterprise innovation, aiming to provide reference for the realization of green and innovative development of enterprises. The study found that the intensity of environmental regulation significantly suppresses the innovation of heavily polluting enterprises. Then the cost of environmental protection investment of enterprises will increase, which may cause the shortage of disposable funds of enterprises, which will reduce the R & D investment in the relationship between environmental regulation and enterprise innovation, indicating that part of the influence of environmental regulation on enterprise innovation is realized through financing constraints.

Influence of Microporous Layers on Interfacial Properties, Oxygen Flow Distribution, and Durability of Proton Exchange Membrane Water Electrolyzers.

The efficient and cost-effective production of green hydrogen is essential to decarbonize heavily polluting sectors such as transportation and heavy manufacturing industries such as metal refining. Polymer electrolyte membrane water electrolysis (PEMWE) is the most promising and rapidly maturing technology for producing green hydrogen at a scale and on demand. However, substantial cost reduction by lowering precious metal catalyst loadings and efficiency improvement is necessary to lower the cost of the produced hydrogen. Porous transport layers (PTLs) play a major role in influencing the PEMWE efficiency and catalyst utilization. Several studies have projected that the use of microporous layers (MPLs) on PTLs can improve the efficiency of PEMWEs, but very limited literature exists on how MPLs affect anodic interfacial properties and oxygen transport in PTLs. In this study, for the first time, we use X-ray microtomography and innovative image processing techniques to elucidate the oxygen flow patterns in PTLs with varying MPL thicknesses. We used stained water to improve contrast of oxygen in PTLs and demonstrate visualization of time averaged oxygen flow patterns. The results show that PTLs with MPLs significantly improve interfacial contact by almost 20% as compared to single layer sintered PTL. For the single layer PTL without MPL, the pore volume utilization for oxygen flow is low and the oxygen follows a viscous fingering flow regime. With MPLs, the pore volume utilization is higher, and the number of oxygen transport pathways is increased significantly. MPLs were also shown to suppress capillary fingering and transition oxygen flow to the viscous fingering regime, which has been proven to decrease site masking effects. Finally, durability tests showed the least voltage degradation for thin MPL and thicker MPLs run into mass transport limitations. Based on these findings, PTL/MPL design optimization strategies are proposed for enabling low catalyst loadings and improving durability.

Work Stressors Before and During COVID-19 Pandemic and Factors Related to Workers in the Heavy Equipment Manufacturing Industry of PT.X

Psychosocial hazards are a major public health problem, so it is necessary to prevent and manage them so as not to cause mental and physical harm to workers. This study aims to determine changes in work stressors before and during the COVID-19 pandemic and related factors to workers in the PT.X Heavy equipment manufacturing industry. The study used a retrospective cohort design from 2018 and 2021 Medical Check-Up (MCU) data with a Stress Diagnosis Survey (SDS) questionnaire. Research was conducted from October 2021 until July 2022 with samples of 146 obtained. Bivariate analysis using proportion and mean test. The research found that the increase in moderate-severe stressors before and during the pandemic was role ambiguity, role conflict, quantitative workload, and career development. On the other hand, qualitative workloads and responsibility for others decreased during the pandemic. The most worsened was role ambiguity and responsibility for others. Based on the type of production and non-production work, there was a significant relationship to quantitative workload before the pandemic (p=0.043), and not significant during the pandemic. Furthermore, there is a significant relationship with qualitative workload during the pandemic (p = 0.043), and it was not significant before the pandemic. It can be concluded that the Pandemic conditions caused an increase and decrease in work stressors analysed in workers in the heavy equipment manufacturing industry.

Evaluation and determinants of total unified efficiency of China's manufacturing sector under the carbon neutrality target

China has one of the largest manufacturing industries in the world. At the same time, the carbon emissions induced by China's manufacturing production pose a severe threat to the environment. With China recently setting the carbon neutrality target, the manufacturing industry faces more urgent pressure to reduce emissions. By adopting the data envelopment analysis, this paper first evaluates the total-factor unified efficiency of China's manufacturing industry at regional and sectoral levels. Then, the panel Tobit model is used to examine the determinants of the efficiency level of China's manufacturing industry. Further, this paper utilizes the economic importance indicator to rank the importance of each factor. The results show regional and sectoral efficiency heterogeneity in China's manufacturing industry. The mid and western China had a slower efficiency growth than the coastal cohort. In addition, the light manufacturing industry showed lower efficiency than the heavy manufacturing industry. Labor quality, industrial agglomeration, and environmental regulation can positively impact efficiency. Surprisingly, our results show that R&D investment and openness harm the manufacturing industry's efficiency. The future policy design should focus on cultivating specialized talent, encouraging point-to-point manufacturing agglomeration, and unifying the emission mandate across the nation. Meanwhile, China should be more cautious of the emissions from foreign-funded manufacturing enterprises and set emission standards on exports of manufactured goods.

Multi-actor perspectives on human robotic collaboration implementation in the heavy automotive manufacturing industry - A Swedish case study

Implementing an industrial collaborative robot for Human-Robot Collaboration (HRC) in the automotive manufacturing industry is an emerging technology-driven solution aiming to increase production efficiency and reduce the human operator's ergonomic load. Successful implementation of innovative technology depends on technical feasibility and on the acceptance by the affected actors. Many studies exist that focus on the technical aspects of HRC, however, research that focuses on understanding the multi-actor concerns of HRC adoption is rare. In an effort to support the successful adoption of industrial collaborative robots, this study aims to understand the concerns of the various actors who work at the operational and management levels influencing future HRC adoption in the heavy automotive manufacturing industry.A literature review was conducted to understand the HRC implementation challenges and the methods used to investigate multi-actor involvement in advance of, and during, the implementation stage. After reviewing existing studies, the actor analysis method was selected to present the actors' perceptions using the action, factor, and goal (AFG) list to understand different actors’ opinions of HRC adoption, using a Swedish heavy vehicle manufacturing company case study.The case study results showed that the actors from the same organization had different concerns but mostly positive expectations for future HRC adoption. The actors’ perception map shows the details pertaining to Actions, Concerns, and Goals as well as the logical flow between these elements in regards to HRC future adoption. The involvement of different actor groups prior to new solution implementation contributes to a holistic view of potential implementation influences and challenges in the organization. Actor analysis can provide a set of analysis processes that comply with multi-actor perceptions to understand future adoption challenges from different perspectives. In the next step, safety-related issues and under-development standardization are the key challenges of HRC implementation.

HYBRID WAR ECONOMIC DETERMINATIONS WHICH FOLLOWED ROMANIA’S FORCED INDUSTRIAL DECLINE

The deindustrialization process of Romania, applied methodically and persistently after the 90s, seems not to be part of the natural path towards industry 4.0, but rather to be a systematic process of planned destruction and erasure of the post-December industry, on a new Valev Plan system conceived in the secret laboratories of the artisans of the new world configuration. The insistence with which there was a systematic and planned demolition of most of the large industrial capacities and platforms betrays obscure interests that can no longer be placed under the umbrella of classifying them as obsolete or non-performing, but rather as inconvenient for foreign markets and foreign capitals. To better understand the mechanisms that acted in order to reset Romania and return it to the status of a semi-agrarian colony, exporting raw materials, natural resources and cheap labor, materialized by the destruction of the heavy, petrochemical, food and car manufacturing industry, we will need to analyze in depth the essence of the manifestation framework of the processes that support globalism as an ideology and globalization as a supra-state and neo-colonialist policy of the great international power centers.

Driving factors and key emission reduction paths of Xinjiang industries carbon emissions: An industry chain perspective

As a typical resource-based region, Xinjiang is under increasing pressure to reduce carbon emissions. The ability to identify the drivers of carbon emissions in the industry and mapping out key emission reduction paths are core components of achieving carbon emission reduction in Xinjiang. This research incorporates energy and environmental factors, constructs a hybrid input–output model of “energy-environment-economy,” and uses the environmental input–output structural decomposition (EIO-SDA) and structural path decomposition (SPD) methods to analyze the drivers of carbon emissions from energy consumption and key emission reduction paths in Xinjiang. First, it shows that the economic-scale effect and the energy-intensity effect are the biggest facilitators of carbon emissions and most significant barriers to carbon emission reduction in Xinjiang. Second, capital formation and domestic trade are the primary sources of demand driving changes in carbon emissions in Xinjiang. Third, sectors involving the production and supply of electricity and heat, such as heavy manufacturing and energy industries, including petroleum processing, coking, nuclear, fuel processing, and chemical industries, are the key sectors responsible for carbon emission reduction in Xinjiang. Last, in terms of industry chains, “metal smelting and rolling processing industry/non-metallic mineral products industry—construction industry—fixed capital formation” and “oil and gas extraction industry (S20)—(intermediate sector)—final demand” are the most important paths driving the growth and decline of carbon dioxide (CO2) emissions from Xinjiang industries, respectively. To promote Xinjiang's carbon emission reduction targets, the Xinjiang government should actively improve its energy structure, promote a change in demand growth patterns, and formulate comprehensive management policies for high-carbon-transfer industries according to an industry chain perspective.

Estimating the Carbon Emissions of Remotely Sensed Energy-Intensive Industries Using VIIRS Thermal Anomaly-Derived Industrial Heat Sources and Auxiliary Data

The energy-intensive industrial sector (EIIS) occupies a majority of global CO2 emissions, but spatially monitoring the spatiotemporal dynamics of these emissions remains challenging. In this study, we used the Chinese province with the largest carbon emissions, Shandong Province, as an example to investigate the capacity of remotely sensed thermal anomaly products to identify annual industrial heat source (IHS) patterns at a 1 km resolution and estimated the carbon emissions of these sources using auxiliary datasets and the boosting regression tree (BRT) model. The IHS identification accuracy was evaluated based on two IHS references and further attributed according to corporate inventory data. We followed a bottom-up approach to estimate carbon emissions for each IHS object and conducted model fitting using the explanatory strength of the annual population density, nighttime light (NTL), and relevant thermal characteristic information derived from the Visible Infrared Imaging Radiometer Suite (VIIRS). We generated a time series of IHS distributions from 2012 to 2020 containing a total of over 3700 IHS pixels exhibiting better alignment with the reference data than that obtained in previous work. The results indicated that the identified IHSs mostly belonged to the EIIS, such as energy-related industries (e.g., thermal power plants) and heavy manufacturing industries (e.g., chemistry and cement plants), that primarily use coal and coke as fuel sources. The BRT model exhibited a good performance, explaining 61.9% of the variance in the inventory-based carbon emissions and possessing an index of agreement (IOA) of 0.83, suggesting a feasible goodness of fit of the model when simulating carbon emissions. Explanatory variables such as the population density, thermal power radiation, NTL, and remotely sensed thermal anomaly durations were found to be important factors for improving carbon emissions modeling. The method proposed in this study is useful to aid management agencies and policymakers in tracking the carbon footprint of the EIIS and regulating high-emission corporations to achieve carbon neutrality.

Economic policy uncertainty and industry portfolio returns in the United States

ABSTRACT This paper examines whether returns on 49 different industry portfolios in the United States (US) expose significantly to the US economic policy uncertainty (EPU) even after controlling for the market and firm-specific risk factors. We find that the US EPU can load significantly against the returns of 15 industry portfolios which include stocks from heavy manufacturing and export dependent industries. However, further asset pricing tests show that the US EPU cannot improve the ability of a benchmark model to capture average industry returns. Additionally, the impact of EPU is time-dependent and significant only during specific periods which are different for each industry. Using a portfolio analysis, we also test whether EPU can forecast future returns. Results imply that the return-EPU relationship is almost flat.

Research on virtual water-embodied energy consumption and efficiency accounting in Liaoning

Due to the extensive development model of "focusing on development with high investment" for a long time, the resources input of industry in Liaoning is seriously mismatched with economic output, resulting in serious waste of resources. In view of this, the consumption of virtual water and embodied energy was calculated through the input-output model, and they were incorporated into the undesired super-SBM to compare the virtual water efficiency, embodied energy efficiency and virtual water-embodied energy coupling efficiency of 23 sectors. Finally, we analyzed the dynamic change in coupling efficiency using the Malmquist index model. The results showed that: (1) Food and Tobacco was the largest consumer of virtual water, accounting for 31.3% of total consumption; Petroleum Product Processing was the largest consumer of embodied energy, accounting for 24.4% of total consumption. (2) Regarding the embodied resource transferring pattern, the total industrial transferrable flux decreased by 40.2% (virtual water) and 12.5% (embodied energy) from 2012 to 2018. Smelting and Pressing of Metals was not only an important supplier but also a significant recipient, receiving metal ore resources and transferring them to different equipment manufacturers. (3) On the whole, the embodied energy efficiency was greater than the virtual water efficiency, but neither had reached the production frontier in most sectors. The coupling efficiency of the overall industry showed a "V" trend, but the efficiency value did not reach 1. (4) Although total factor productivity (TFP) and the corresponding decomposition factors were significantly different in 23 sectors, pure technical efficiency (PEC) obviously restricted TFP in most sectors. In addition, scale efficiency (SEC) maintained a stable balanced, especially in heavy manufacturing industry. In contrast, technology efficiency (TC) severely constrained TFP especially in Chemical Products and Production and Supply of Water.

Elasticity of substitution and biased technical change in the CES production function for China's metal-intensive industries

To achieve sustainable and green development, it is imperative for China, as the world's major metal consumer, to improve utilization efficiency and conservation of metal resources. Thus, understanding the industrial endogenous growth patterns of China regarding metal utilization and technical change becomes the prerequisite. Therefore, this paper regards metal as one of production factors nested with capital and labor, employs normalized supply-side system approach to estimate the elasticity of substitution in constant elasticity of substitution (CES) function and analyzes technical change bias based on the analytical framework built in this paper. Results show that: the optimal nesting structure for most metal-intensive industries are metal-capital composite nested with labor. And the metal input is less efficient than capital or labor in all metal-intensive industries. The technical change biases for metal-intensive industries are diversified, but only metal mining industries and heavy machinery manufacturing industries tend to save metal when expanding the production effectively. Targeted suggestions are made per industry according to the heterogeneity of production factors allocation and technical change biases.

Combinatorial Growth with Physical Constraints: Evidence from Electronic Miniaturization

In the past sixty years, transistor sizes and weights have decreased by 50 percent every eighteen months, following Moore’s Law. Smaller and lighter electronics have increased productivity in virtually every industry and spurred the creation of entirely new sectors of the economy. However, while the effect of the increasing quality of computers and electronics on GDP has been widely studied, the question of how electronic miniaturization affects economic growth has been unexplored. To quantify the effect of electronic miniaturization on GDP, this paper builds an economic growth model that incorporates physical constraints on firms’ production sets. This model allows for new types of productivity spillovers that are driven by products’ physical characteristics. Not only are there spillovers from changes in industry productivity, but also, there can be “size spillovers,” where the miniaturization of one industry’s product leads to miniaturization of products that are downstream in the supply chain, reflecting how transistor miniaturization has led to the decrease in size of a large variety of electronic products. Using a new data set of product weights and sizes, we test the predictions of the model and show that Moore’s Law accounts for approximately 3.5 percent of all productivity growth in the 1982-2007 period, and for 37.5 percent of the productivity growth in heavy manufacturing industries. The results are robust under multiple specifications, and increase in strength during the 1997-2007 subperiod.

Assessment of Musculoskeletal discomfort for mobile crane operators

Workers seated in mobile cranes and operating for a prolonged period with an awkward posture are facing various ergonomic problems in the different body parts and particularly in the lower back. The research study purpose is to find an association of discomfort with the mobile crane operations. A discomfort study was carried out in a heavy equipment manufacturing industry where most of the mobile crane operators are continuously suffering from musculoskeletal discomfort in different body parts. Discomfort information was obtained with the help of a body part discomfort questionnaire during the various shift intervals from the start to the end of the shift. A total of 30 mobile crane operators of age from 21 to 59 years were made to participate. The study results reveals that, among the 30 mobile crane operators, 83.3% of operators reported discomfort in the lower back, and 20.0% reported in the upper back. In other parts, 23.3% to 63.3% of operators reported discomfort. Considering the severity level of discomfort reported by the operators, the highest discomfort is seen in the lower back and neck region. The operator’s age also has a significant influence on body discomfort sensed by mobile crane operators. Concluded that the main effected body parts are lower back and neck and the risk factors that may cause this discomfort are an awkward posture and whole-body vibration.

Chinese cities exhibit varying degrees of decoupling of economic growth and CO2 emissions between 2005 and 2015

Summary Cities, contributing more than 75% of global carbon emissions, are at the heart of climate change mitigation. Given cities' heterogeneity, they need specific low-carbon roadmaps instead of one-size-fits-all approaches. Here, we present the most detailed and up-to-date accounts of CO2 emissions for 294 cities in China and examine the extent to which their economic growth was decoupled from emissions. Results show that from 2005 to 2015, only 11% of cities exhibited strong decoupling, whereas 65.6% showed weak decoupling, and 23.4% showed no decoupling. We attribute the economic-emission decoupling in cities to several socioeconomic factors (i.e., structure and size of the economy, emission intensity, and population size) and find that the decline in emission intensity via improvement in production and carbon efficiency (e.g., decarbonizing the energy mix via building a renewable energy system) is the most important one. The experience and status quo of carbon emissions and emission-GDP (gross domestic product) decoupling in Chinese cities may have implications for other developing economies to design low-carbon development pathways.

A qualitative study on industry 4.0 competitiveness in Turkey using Porter diamond model

Purpose: Industry 4.0 offers a new network approach by using advanced Information and Communication Technologies (ICT) and for manufacturing industries in particular. This paper analyzes the understandings of heavy manufacturing industry in Turkey about the concept of Industry 4.0 as well as its significance of in nation’s competitiveness. The study applies in Porter’s Diamond Model as a framework in order to provide a dynamic view of Industry 4.0 in nation’s competitive advantage.Design/methodology/approach: The results of semi structured interviews are examined in the framework and common understandings are compared with existing literature.Findings: The analysis indicates that, the heavy manufacturing companies are aware of the topic of Industry 4.0 in general in terms of its definition, future aspects and possible benefits and challenges. It has been observed that factor conditions (labor and capital) are the most important aspects which affect development of Industry 4.0 competitiveness in Turkey. Although the country is still in initial stage on its competitive position; the effects of the government and some chances might increase its competitiveness in the future.Originality/value: Regarding different research on Industry 4.0, this paper gives an insight in development path of Industry 4.0 competitiveness especially for the developing countries. There is still lack of empirical research on nations’ competitiveness on Industry 4.0; therefore, this paper deepens the concept for further research and action plans for the path of competitiveness.

Structural Health Monitoring (SHM) of Machine Using a Combination of Non-Destructive Testing for Heavy Manufacturing Industry

Markets are affected by assorted consumer requirements, which insist on superior quality, shorter delivery time, better customer support, and lower prices. Simultaneously, product life cycles are becoming shorter. Success relies on having either a cost-benefit or a value benefit, or, both in any competitive context. Therefore, non-destructive techniques (NDT) become vital but in the conventional system, the maintenance personnel has to visit the machine that consumes time and energy. In the present COVID-19 situation and to save energy and time, there is a necessity of making condition monitoring contactless as much as possible. Therefore, in this research work, a structural health monitoring analysis presented that covers: firstly, enlisting of the NDT infrastructure commonly available in heavy manufacturing industries; secondly, common causes and reasons of machine failures and finally, discusses need of embedded structural health monitoring (e-SHM) system with the combination of NDT in place of existing monitoring practice. The presented work suggested that a combination of NDT with e-SHM is better for timely fault detection to ensure effective condition monitoring.