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•This study analyzes and compares the distribution of inorganic acid emissions from each unit of the semiconductor process.•HF emissions are primarily from the CVD process, HCl ...emissions predominantly come from the DIFF process, all H3PO4 emissions are attributed to the EPI process and H2SO4 emissions are mainly produced by the wet etching process.•It was found that 82–99 % of the inorganic acid emissions were in the form of solid particles with a particle size of less than 1 µm from the LSC.
Inorganic acids, widely used in semiconductor manufacturing processes, have become a concern as improper handling of these acids can have severe environmental impacts. This study investigates the major contamination source of inorganic acids (hydrofluoric acid, hydrochloric acid, nitric acid, phosphoric acid, and sulfuric acid), the different ratios of solid and gaseous inorganic acids, and the particle size distribution of solid particles emitted after local scrubber (LSC) treatment. An assessment of pollutant status revealed that hydrofluoric acid emissions dominate in the chemical vapor deposition (CVD) process at 65%, hydrochloric acid in the diffusion (DIFF) process at 69%, phosphoric acid in the epitaxy (EPI) process at 100%, and sulfuric acid in wet etching at 85%. In contrast, particulate matter constitutes the primary component, ranging from 82% to 99% of the LSC emission. The LSC configuration is then adjusted based on the overview of inorganic acid emissions from different processes to match their characteristics. After related improvement activities, the results presented a significant reduction of 56% to 87% in inorganic acid emissions at the outlet of the LSC, and 18-68% reduction in the stack emissions.
•Review of the ongoing research on BDA in manufacturing process.•Proposition of a framework grouping BDA capabilities in manufacturing process.•Identification of research trends in implementing BDA ...in manufacturing process.•Conducting multiple case studies of the application of BDA in real-life context of the manufacturing process in a leading manufacturers of phosphate derivatives.•Drawing a set of recommendations based on the findings of the multiple case study.
Today, we are undoubtedly in the era of data. Big Data Analytics (BDA) is no longer a perspective for all level of the organization. This is of special interest in the manufacturing process with their high capital intensity, time constraints and given the huge amount of data already captured. However, there is a paucity in past literature on BDA to develop better understanding of the capabilities and strategic implications to extract value from BDA. In that vein, the central aim of this paper is to develop a novel model that summarizes the main capabilities of BDA in the context of manufacturing process. This is carried out by relying on the findings of a review of the ongoing research along with a multiple case studies within a leading phosphate derivatives manufacturer to point out the capabilities of BDA in manufacturing processes and outline recommendations to advance research in the field. The findings will help companies to understand the big data analytics capabilities and its potential implications for their manufacturing processes and support them seeking to design more effective BDA-enabler infrastructure.
Thin films of Linear Low-Density Polyethylene are used for stratospheric balloon applications. They undergo tensile mechanical stress on a wide range of temperatures -95; 55°C. The aim of this study ...is to compare the influence of blown film and double-bubble manufacturing processes on the crystalline phase and mechanical properties of the films through their operating temperatures (flight, storage, and transportation temperatures). Dynamic Mechanical Analysis and Differential Scanning Calorimetry have been used to monitor the dynamic mechanical properties in tension mode and the crystalline phase of the films respectively. The films mechanical properties are dependent on their manufacturing process. The double-bubble process allows isotropic tensile mechanical properties regarding stretching direction, whereas the blown film process favors only transversal direction. To simulate different storage conditions, annealing has been performed. The influence of annealing on the tensile mechanical properties of the films depends mainly on the internal stress stored during manufacturing. The double-bubble process produces a biaxially stretched film with a higher stretching ratio than blown films. The dissipated internal stress can be associated with thermal shrinkage and goes up to 10 % for the biaxially stretched film. The more internal stress is stored, the more E′ and E″ increases. Annealing also favors the formation of a secondary crystalline phase that is dependent on annealing temperature and time, and exhibits αc relaxation. After annealing, the amorphous phase is less stretched, and the crystalline phase keeps its orientation.
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•Thermostimulated creep has been used to observe polyethylene's sub-γ relaxation mode.•Biaxial stretching produces films with isotropic tensile mechanical properties.•Annealing can improve tensile mechanical properties of polyethylene films.•Annealing produces secondary-crystalline phase.•Annealing allows strong internal stress relaxation for biaxially stretched polyethylene film.
Oolong tea is a typical semi-fermented tea and is famous for its unique aroma. The aim of this study was to compare the volatile compounds during manufacturing process to reveal the formation of ...aroma. In this paper, a method was developed based on head-space solid phase microextraction/gas chromatography–mass spectrometry (HS-SPME/GC–MS) combined with chemometrics to assess volatile profiles during manufacturing process (fresh leaves, sun-withered leaves, rocked leaves and leaves after de-enzyming). A total of 24 aroma compounds showing significant differences during manufacturing process were identified. Subsequently, according to these aroma compounds, principal component analysis and hierarchical cluster analysis showed that the four samples were clearly distinguished from each other, which suggested that the 24 identified volatile compounds can represent the changes of volatile compounds during the four steps. Additionally, sun-withering, rocking and de-enzyming can influence the variations of volatile compounds in different degree, and we found the changes of volatile compounds in withering step were less than other two manufacturing process, indicating that the characteristic volatile compounds of oolong tea might be mainly formed in rocking stage by biological reactions and de-enzyming stage through thermal chemical transformations rather than withering stage. This study suggested that HS-SPME/GC–MS combined with chemometrics methods is accurate, sensitive, fast and ideal for rapid routine analysis of the aroma compounds changes in oolong teas during manufacturing processing.
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•SPME/GC-MS combined with chemometrics were used to analyze the aroma compounds during manufacturing process of oolong tea.•A total of 24 aroma compounds showing significant differences during manufacturing process.•The characteristic volatiles of oolong tea might be formed in rocking and de-enzyming stages rather than withering stage.
The electrochemical micromachining in non-conventional machining which suffers from process control in micro level. In addition, the work material i.e. stainless steel provides high strength, high ...toughness and adherence to tool material, hence machining of such material is arduous. However, the use of stainless steel offers its availability in the field of aerospace fuel injection and orthodontic application, since it possess superior qualities. In this paper, the optimization of micro drilling process is carried out in stainless steel by considering certain metrics like feed rate, voltage and duty ratio. The geometric characteristics to drill the tool depends on response parameters like overcut, removal rate of material and conicity. Such parameter determines both the geometric and machining characteristics of the drill bit. The study is evaluated to observe the effect of response and duty ratio parameters such as material removal rate (MRR), machining time and overcut. Further, the conicity is analyzed using VMS images. Finally, the proposed work establishes duty cycle in pulsed electrochemical micromachining domain of hard materials and tests its performance.
The goal of this paper is to present an innovative conception how to use metrisable vector structure of a manufacturing process, based on quantitative relations between the activity of input streams, ...features of the product, and effect of losses; all of which are excellent practical solution for Industry 4.0, and in turn intelligent factories. This solution can be a usefull way in the process of building sustainable organization. A vector representation of manufacturing processes was formulated, one which is based in system engineering. Three manufacturing system state vectors were proposed. These are: input stream vector
ϕ
, product features vector
P
→
which is also referred to as quality vector, and losses vector
S
→
. Scalar, vector, and mixed products of these vectors may form constitutive equations of manufacturing processes. The relations between the vectors
ϕ
,
P
→
,
S
→
provide a possibility for a metrisable, complex analysis and assessment of a contemporary manufacturing process. The paper shows practical methods for defining the size of the vector values within the process. The demonstrated vector description of stream-systemic processes can also be applied to non-material manufacturing.
Manufacturing process related functionalities, like optimization and control, are in general demanding in terms of data, computational time and efficiency. However, there are no generic certification ...or validation schemes that can be followed. In particular, only ISO application can verify the suitability of operations up to an extent. The current work utilizes an enhanced version of Blockchain so that functionalities at the process level can be certified as per a particular scheme. The concept of ledger is elaborated to this end, to manipulate knowledge and be able to handle it like an asset that is exchanged. Thus, a specific generic framework is proposed, herein, to reassure that the right kind of information has been exchanged during process control and optimization. Furthermore, expert distributed agents are utilized to turn knowledge into certified procedures. Encryption issues are also regarded, providing safety and security as extra characteristics. The case study of thermal process control is regarded in this sense to prove the complementary character of these concepts and the usability of the framework. Finally, the existence of additional features within this loop is discussed, like the validation of quantifying concepts like resource streams.
Powder spreading is a key step in the powder-bed-based additive manufacturing process, which determines the quality of the powder bed and, consequently, affects the quality of the manufactured part. ...However, powder spreading behavior under additive manufacturing condition is still not clear, largely because of the lack of particle-scale experimental study. Here, we studied particle-scale powder dynamics during the powder spreading process by using in-situ high-speed high-energy x-ray imaging. Evolution of the repose angle, slope surface speed, slope surface roughness, and the dynamics of powder clusters at the powder front were revealed and quantified. Interactions of the individual metal powders, with boundaries (substrate and container wall), were characterized, and coefficients of friction between the powders and boundaries were calculated. The effects of particle size on powder flow dynamics were revealed. The particle-scale powder spreading dynamics, reported here, are important for a thorough understanding of powder spreading behavior in the powder-bed-based additive manufacturing process, and are critical to the development and validation of models that can more accurately predict powder spreading behavior.
The evolutionary optimisation algorithms appeared as an effective alternative to conventional statistical methods that have certain limitations in optimising complex manufacturing processes. ...Considering works published in the last decade, this paper presents an analysis of the particle swarm optimisation (PSO) implementation in designing parameters of heterogeneous manufacturing processes, both conventional and emerging, new processes. The literature review and analysis was structured according to the complexity of the optimisation problem (single response and multiresponse problems), and the development of an objective function for PSO. The tuning of the PSO algorithm-specific parameters was analysed in detail. The PSO algorithm performance was benchmarked with the results of other methods, including evolutionary algorithms, in designing process parameters. The concerns in applying PSO for multiresponse manufacturing problems were highlighted, and recommendations for future research were drawn. Such a comprehensive review on the PSO application in optimising manufacturing processes, including the detailed discussion on the algorithm characteristics and benchmark with other optimisation procedures, has not been pursued so far. Therefore, this review analysis provides hands on information for researchers and engineers at one place, and it is believed that the findings could serve as a basis for the future research and implementation directions.
•Comprehensive and critical analysis of PSO usage in process optimisation is shown.•Issues and concerns in PSO application for process parameter design are identified.•PSO specific parameters are discussed in detail, according to the problem types.•Detailed comparison with other EAs, in terms of accuracy and speed, is presented.•Critical remarks, findings, issues and recommendation for future research are given.
Economical, environmental and legislative drivers have recently raised the awareness of energy consumption and the associated environmental impact of manufacturing processes. A reliable prediction of ...unit process energy consumption will enable industry to develop potential energy saving strategies during product design and process planning stages. This paper presents an empirical model to characterize the relationship between energy consumption and process variables for material removal processes. The methodology has been tested and validated on a number of turning and milling machine tools. The model presented predicts the energy consumption of manufacturing processes with an accuracy of more than 90%.
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