Industrial Welding Research Articles

Improved productivity by reduced variation in gas metal arc welding (GMAW)

The purpose of the research conducted is to describe the consequences of variation in the welding industry and the effect it has on manufacturing productivity. The potential has shown to be hidden in unnecessarily stringent requirements and over-processing. This has been studied in steps: customer requirements, design and analysis, preparation, welding, and assessment. The effect of variation in each step has been analyzed including estimations of its productivity improvement potential. Theoretically, in a perfect situation, with customized requirements and eliminated variation, more than half of all welding could be removed. Such a reduction is certainly neither practical nor possible. However, a sensible, controlled reduction could still have a very high impact. The financial implications are therefore substantial. The improved productivity of the manufacturing resources could be used for business development and increased production. To be able to realize the potential, interdisciplinary efforts are necessary. Management across different functions need to agree on the intended product life and make decisions thereafter.

Barriers for industrial implementation of in-process monitoring of weld penetration for quality control

The research conducted sheds a light on the question why robust in-process monitoring and adaptive control are not fully implemented in the welding industry. In the research project FaRoMonitA, the possibilities to monitor the weld quality during welding have been investigated. Research conducted in this area has merely focused on technical issues investigated in a laboratory environment. To advance the research front and release some barriers related to industrial acceptance, the studies conducted in this paper have been both quantitative and qualitative in form of experiments combined with an interview study. The quality property weld penetration depth was chosen for in-process monitoring to evaluate the industrial relevance and applicability. A guaranteed weld penetration depth is critical for companies producing parts influenced by fatigue. The parts studied were fillet welds produced by gas metal arc welding. The experiments show that there is a relationship between final penetration depth and monitored arc voltage signals and images captured by CMOS vision and infrared cameras during welding. There are still technical issues to be solved to reach a robust solution. The interview study indicates that soft issues, like competence and financial aspects, are just as critical.

Strength and Durability of 8M, 10M, 12M Geo – Polymer Concrete

The major problem the world is facing today is the environmental pollution. In the construction industry mainly the production of Portland cement will causes the emission of pollutants results in environmental pollution. We can reduce the pollution effect on environment, by increasing the usage of industrial by-products in our construction industry. Geo-polymer concrete is such a one and in the present study, to produce the geo-polymer concrete the Portland cement is fully replaced In this research some material such as1. Industrial Weld Slag waste with NAOH Solutions 2. M Sand NAOH Solutions 3. Fly ash NAOH Solutions among the three on mixed with conventional material of Fine aggregate and Coarse aggregate and Bottom ash waste along with fly ash with were used for better utilization in Cement Concrete works. The above Three mix ratio which one become a higher strength. It decreases the overall CO2 consumption and increases the workability of concrete; as a result it improves strength and durability.

A new concept of universal substitutive explosive welding

This paper presents an innovative explosive welding technology, namely Universal Substitutive Explosive Welding technique, which was recently developed by Australian Defence Science and Technology Group to improve the survivability and mobility of military vehicles. The new technique is superior to the existing industrial explosive welding ones in terms of integrity, quality and stability. It is able to significantly upgrade the hardness upper limit of target material and ensure the perfect welding bond between the flyer (soft) and target (hard) panels without size limitation of target panel. Experimental results show that using the new technique raised the ballistic velocity limit (V50) of the explosively welded panel by up to 20% and reduced the bulge depth (related to dynamic plasticity) significantly without any rupture or fragmentation issues. Charpy impact test on the sample fabricated by the new technique showed strong recovery effects with time with no transition temperature.

A hybrid multi-objective grey wolf optimizer for dynamic scheduling in a real-world welding industry

Welding is one of the most important technologies in manufacturing industries due to its extensive applications. Welding scheduling can affect the efficiency of the welding process greatly. Thus, welding scheduling problem is important in welding production. This paper studies a challenging problem of dynamic scheduling in a real-world welding industry. To satisfy needs of dynamic production, three types of dynamic events, namely, machine breakdown, job with poor quality and job release delay, are considered. Furthermore, controllable processing times (CPT), sequence-dependent setup times (SDST) and job-dependent transportation times (JDTT) are also considered. Firstly, we formulate a model for the multi-objective dynamic welding scheduling problem (MODWSP). The objectives are to minimize the makespan, machine load and instability simultaneously. Secondly, we develop a hybrid multi-objective grey wolf optimizer (HMOGWO) to solve this MODWSP. In the HMOGWO, a modified social hierarchy is designed to improve its exploitation and exploration abilities. To further enhance the exploration, genetic operator is embedded into the HMOGWO. Since one characteristic of this problem is that multiple machines can handle one operation at a time, the solution is encoded as a two-part representation including a permutation vector and a machine assignment matrix. To evaluate the effectiveness of the proposed HMOGWO, we compare it with other well-known multi-objective metaheuristics including NSGA-II, SPEA2, and multi-objective grey wolf optimizer. Experimental studies demonstrate that the proposed HMOGWO outperforms other algorithms in terms of convergence, spread and coverage. In addition, the case study shows that this method can solve the real-world welding scheduling problem well.

Effects of manganese exposure on crayfish motility.

Manganese (Mn) is a metal ion that is essential for healthy brain functioning at low levels (Quintanar, 2008). However, excessive exposure to Mn can lead to manganism — a neurodegenerative disease that manifests in Parkinsonian symptoms. High levels of Mn are found in hazardous occupational environments, especially in the mining and welding industries. In addition to the Parkinsonian symptoms associated with exposure to high levels of Mn, low to moderate Mn exposure has been linked with subtle impairments, such as hyperactivity and decreased cognitive abilities (Neal and Zheng, 2015). These low to moderate exposures can occur due to unregulated Mn levels in public tap water, which is especially prone to infiltration of neurotoxic chemicals in regions with high levels of mining activity (Quintanar, 2008). It was hypothesized that low to moderate Mn exposure in crayfish would be associated with altered motility in a T-maze. Crayfish exposed to varying levels of Mn were tested in a two-arm T-maze with a lighted arm and a dark arm. Movements and behavior were analyzed with video tracking software EthoVision XT 11. Behaviors of interest, including place preference to maze zones, choice behaviors, and general activity levels were recorded. We expect that Mn exposure will be associated with significant deficits in crayfish motility, which can be inferred to affect decision-making and risk-taking behaviors.

Changes in morphology of adult neural stem cells following low-level manganese exposure in vitro.

Adult neural stem cells (NSCs) are neural progenitor cells that differentiate into neurons and glial cells in the brain throughout an organism’s life. The sub ventricular zone(SVZ) in mammals holds a niche of NSCs that are involved in neurologic plasticity, brain damage repair, behavioral response to stimuli, and learning and memory formation. Cultured SVZ-derived NSCs offer an accessible model for investigating the cellular and molecular mechanisms in brain function.Manganese causes neuronal dysfunction, but its cellular mechanisms are unknown. While exposure to manganese results in a neurodegenerative condition known as manganism that mimics symptoms of idiopathic Parkinson’s Disease, people living in mining and industry communities are chronically exposed to manganese through drinking water or inhalation at levels below EPA limits. We are investigating the effects of such low-level manganese on cellular functions of neural cells. The investigation is directed towards examining changes in intracellular signaling pathways and cellular mechanisms in adult NSCs exposed to manganese of adult neurogenesis. We found that MnCl2 impairs normal development and proliferation of neural stem cell behavior. Cultured adult NSCs from the SVZ displayed abnormal morphology when exposed to 500uM and 800uM concentrations of MnCl2 for 24 hours. However, the manganese concentrations causing morphology impairment do not undergo apoptosis. Excess manganese exposure is a concern for West Virginia due to the abundance of welding, mining, and metal manufacturing industries in the area. This research recognizes the unique vulnerability of the brain to manganese and could be used for regulation of manganese exposure limits.

Discrimination of particulate matter emission sources using stochastic methods

Abstract Particulate matter (PM) is one of the criteria pollutants which has been determined as harmful to public health and the environment. For this reason the ability to recognize its emission sources is very important. There are a number of measurement methods which allow to characterize PM in terms of concentration, particles size distribution, and chemical composition. All these information are useful to establish a link between the dust found in the air, its emission sources and influence on human as well as the environment. However, the methods are typically quite sophisticated and not applicable outside laboratories. In this work, we considered PM emission source discrimination method which is based on continuous measurements of PM concentration with a relatively cheap instrument and stochastic analysis of the obtained data. The stochastic analysis is focused on the temporal variation of PM concentration and it involves two steps: (1) recognition of the category of distribution for the data i.e. stable or the domain of attraction of stable distribution and (2) finding best matching distribution out of Gaussian, stable and normal-inverse Gaussian (NIG). We examined six PM emission sources. They were associated with material processing in industrial environment, namely machining and welding aluminum, forged carbon steel and plastic with various tools. As shown by the obtained results, PM emission sources may be distinguished based on statistical distribution of PM concentration variations. Major factor responsible for the differences detectable with our method was the type of material processing and the tool applied. In case different materials were processed by the same tool the distinction of emission sources was difficult. For successful discrimination it was crucial to consider size-segregated mass fraction concentrations. In our opinion the presented approach is very promising. It deserves further study and development.

Manganese and aging

Manganese (Mn) is an essential metal that is required as a cofactor for many enzymes and is necessary for optimal biological function. Mn is abundant in the earth’s crust and is present in soil and well water. Mn is also found in industrial settings, including mining, welding, and battery manufacture. Mn is also present in infant formula, parenteral nutrition, as well as pesticides and gasoline additives. A sufficient amount of Mn is obtained from most diets, and Mn deficiency is exceedingly rare. Excessive exposure to Mn in high doses can result in a condition known as manganism that results in psychological and emotional disturbances and motor symptoms that are reminiscent of Parkinson’s disease, including gait disturbance, tremor, rigidity, and bradykinesia. Treatment for manganism is to remove the patient from Mn exposure, though symptoms are generally irreversible. The effects of exposure to Mn at lower doses are less clear. Little work has been done to evaluate the effects of chronic exposure to subclinical levels of Mn, especially in regard to lifelong exposures and the effects on the aging process. Mn is known to have effects on some of the same mechanistic processes that are altered in aging. This review will describe the general effects of Mn exposure and will focus on how Mn may be related to some of the mechanism of aging: neurogenesis, oxidative stress, and microglial activation and inflammation.

CAOS-CMOS camera

Proposed and experimentally demonstrated is the CAOS-CMOS camera design that combines the coded access optical sensor (CAOS) imager platform with the CMOS multi-pixel optical sensor. The unique CAOS-CMOS camera engages the classic CMOS sensor light staring mode with the time-frequency-space agile pixel CAOS imager mode within one programmable optical unit to realize a high dynamic range imager for extreme light contrast conditions. The experimentally demonstrated CAOS-CMOS camera is built using a digital micromirror device, a silicon point-photo-detector with a variable gain amplifier, and a silicon CMOS sensor with a maximum rated 51.3 dB dynamic range. White light imaging of three different brightness simultaneously viewed targets, that is not possible by the CMOS sensor, is achieved by the CAOS-CMOS camera demonstrating an 82.06 dB dynamic range. Applications for the camera include industrial machine vision, welding, laser analysis, automotive, night vision, surveillance and multispectral military systems.

Application of Expectation Maximization Method for Purchase Decision-Making Support in Welding Branch

Abstract The article presents a study of applying the proposed method of cluster analysis to support purchasing decisions in the welding industry. The authors analyze the usefulness of the non-hierarchical method, Expectation Maximization (EM), in the selection of material (212 combinations of flux and wire melt) for the SAW (Submerged Arc Welding) method process. The proposed approach to cluster analysis is proved as useful in supporting purchase decisions.

Facilitating decision-making by choosing an NDT method based on information need

This paper discusses the choice of an NDT method (non-destructive testing) from an information need perspective. It bridges the gap between technical methods, monitoring procedures and the need for information in an industrial application. The simple pull approach described starts from the decision that needs to be taken rather than from a previous data push procedure. That makes it more likely to match the method with the actual need, which leads to more effective and efficient evaluations. The pull approach is described by using a case from the welding industry, evaluation of the weld toe radius. The toe radius, defining how smooth the transition between the plate and the weld is, has been found critical to fatigue strength. Depending on the internal customer’s need of information, various evaluation solutions are preferred. The methods range from manual gauges to fully automated camera solutions. An interview study performed shows that the current process for choosing evaluation method differs. The person needing the information is often not the starting point in the process. A change in starting point influences both the choice of NDT method and visualization and thereby how efficient and effective the decision-making support will be. The financial effect is significant.

An Algorithm and Simulation for the Automatic Welding of Battery Cover

In view of the current welding industry, there is no automated programming tool for the welding path of square battery cover. According to differential geometry theory, the principle of nonlinear error is analyzed. Then a simplified model for nonlinear error is established. Based on these, an efficient algorithm based on nonlinear error is proposed. According to the proposed algorithm, two instantiation of the algorithm are presented. Therefore, the proposed algorithm is simple, reliable, and efficient. It adapts to the requirement of two mainstream spuare battery covers perfectly.

The Structure and Mechanical Properties of Bridge Steel Weldings With Glass-Steel Liners

A new technology is developed for welding multi-span bridge constructions. The mechanical properties and structure of the low-carbon bridge steel welds have been studied. The welding parameters and application of steel-glass liners provide for long-term service of steel constructions in conformity with the welding industry specifications.

Solid State Welding and Application in Aeronautical Industry

In this study solid state welding and application in aeronautic industry have been researched. The solid state welding technic is used in the industrial production fields such as aircraft, nuclear, space industry, aeronautic industry, etc., actually solid state welding is a process by which similar and dissimilar metals can be bonded together. Hence a material can be created as not heavy but strong strength. Beside, advantages and disadvantages of solid state welding have been discussed. Also the diffusion welding and friction welding which belong to the solid state welding is observed in aeronautic industry.

A vision-based system for post-welding quality measurement and defect detection

The measurement of the welding bead and the followed evaluation of the weld quality is an important part in the industrial welding. However, the main difficulty in using visual inspection to evaluate the weld quality is the time taken and labor wasted. In order to solve these problems, an automated vision-based system is presented for non-destructive and online post-welding quality inspection. The trouble with respect to vision-based system is the robustness of image processing algorithms. This paper presents a novel image processing method that can automatically extract the weld joint profile and feature points, measure the weld bead size, and detect defects. At the same time, the three-dimensional (3D) profile of the weld surface can be reconstructed with the aim of monitoring the weld quality online. The proposed algorithm is validated through experiment in industrial environment.

Towards Energy Optimization Using Trajectory Smoothing and Automatic Code Generation for Robotic Assembly

In automated industrial production, the effciency of robotic motions directly affects both the final throughput and the energy consumption. By simulating and optimizing robot trajectories, cycle times and energy consumption can be lowered, or redundant robots can be detected. Here a polynomial basis function trajectory parametrization is presented, which enables direct export to executable robot code, and reduces the number of variables in the optimization problem. The algorithm finds time-optimal trajectories, while including collision avoidance and fulfilling joint, velocity and acceleration limitations. Applied torques are used as an approximation of the energy consumption to analyse the smooth trajectories, and successful tests show potential reductions of 10% for a standard industrial robot stud welding station.

Python and MatPlotLib based Open Source Software System for Simulating Images with point Light Sources in Attenuating and Scattering Media

Simulating images of various objects in a real world scene has wide applications while testing algorithms for machine vision applications as well as in computer graphics and gaming software industry. Most current algorithms use collimated light sources and assume the medium to be non-scattering and non-attenuating. In real world, most light sources are too near to the objects in the scene and hence cannot be assumed to be collimated. Real world mediums, such as oceans in case of Underwater Robotic Vehicle (URV) applications or smoke and vapor filled air in case of industrial welding applications, scatter and attenuate light. A software system that makes no such assumptions and uses point light sources in scattering and attenuating media has been developed. Another novelty of current work is use of open source Python programming language along with associated 2D graphics and plotting library, MatPlotLib. General Terms Underwater Robotic Vehicles, Industrial Robots, Image simulation, Python, MatPlotLib.

Sensors and their classification in the fusion weldingtechnology

In this paper the most commonly used sensing systems in modern welding industry, which nowadays includes robotic systems, are listed and analyzed. According to mechanisms of action and measured parameters, several classifications of sensor systems have been presented. MIG/MAG, resistance and laser beam welding processes are the most commonly robotized ones in the industry and therefore special attention has been given to them. Several characteristic, limitations and advantages of sensor systems are presented and mechanisms of action are briefly described.

Simulation and Practical Analysis on Power Factor Correction Techniques for Welding Applications

The most of the industrial welding applications involving of electronic circuits such as AC-DC, and DC-AC and AC-DC converters. The input power factor of such a system is reduced due to the presence of more harmonics due to the non-linear devices within the converters which leads to creates more adverse effects. There by a need of suitable AC-DC converter with power factor correction technique to condition the supply current. The power factor correction rectifier that requires best current control from i) Peak current control ii) Average current control and iii) Hysteresis current control. This paper presents a comparative analysis from above mentioned power factor correction control topologies. The simulation of these control techniques are carried out using “Plecs” with “MATLAB/SIMULINK”. The simulation results shows that Hysteresis control has low THD, good DC link voltage regulation and better performance than other control techniques. The same control technique is implemented in TMS320F2812 DSP and results are proved.