Search results for: hardwood lumber manufacturing process

Authors: Paul Ihuoma Oluikpe

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The purpose of this paper is to explore and highlight the process of creating value for strategy management by embedding knowledge management in the business process. Knowledge management can be seen from a three-dimensional perspective of content, connections and competencies. These dimensions can be embedded in the knowledge processes (create, capture, share, and apply) and operationalized within a business process to effectively create a scenario where knowledge can be focused on enabling a process and the process in turn generates outcomes. The application of knowledge management on business processes of organizations is rare and underreported. Few researches have explored this paradigm although researches have tended to reinforce the notion that competitive advantage sits within the internal aspects of the firm. Given this notion, it is surprising that knowledge management research and practice have not focused sufficiently on the business process which is the basic unit of organizational decision implementation. This research serves to generate understanding on applying KM in business process using a large multinational in Sub-Saharan Africa.

Keywords: knowledge management, business process, strategy, multinational

Procedia PDF Downloads 693

Authors: A. Anbu Raj, V. Mugendiren

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Sheet metal forming is a vital manufacturing process used in automobile, aerospace, agricultural industries, etc. Incremental forming is a promising process providing a short and inexpensive way of forming complex three-dimensional parts without using die. The aim of this research is to study the forming behaviour of AA 5052, Aluminium Alloy, using incremental forming and also to study the FLD of cone shape AA 5052 Aluminium Alloy at room temperature and various annealing temperature. Initially the surface roughness and wall thickness through incremental forming on AA 5052 Aluminium Alloy sheet at room temperature is optimized by controlling the effects of forming parameters. The central composite design (CCD) was utilized to plan the experiment. The step depth, feed rate, and spindle speed were considered as input parameters in this study. The surface roughness and wall thickness were used as output response. The process performances such as average thickness and surface roughness were evaluated. The optimized results are taken for minimum surface roughness and maximum wall thickness. The optimal results are determined based on response surface methodology and the analysis of variance. Formability Limit Diagram is constructed on AA 5052 Aluminium Alloy at room temperature and various annealing temperature by using optimized process parameters from the response surface methodology. The cone has higher formability than the square pyramid and higher wall thickness distribution. Finally the FLD on cone shape and square pyramid shape at room temperature and the various annealing temperature is compared experimentally and simulated with Abaqus software.

Keywords: incremental forming, response surface methodology, optimization, wall thickness, surface roughness

Procedia PDF Downloads 338

Authors: Auliya Adzillatin Uzhma, M. Adrian Rizky, Puri Diah Santyarini

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Bekasi Industrial Area in Kab. Bekasi and SEZ (Special Economic Zone) Sei Mangkei in Kab. Simalungun are two areas whose have the same main economic activity that are manufacturing industrial. Manufacturing industry in Bekasi Industrial Area contributes more than 70% of Kab. Bekasi’s GDP, while manufacturing industry in SEZ Sei Mangkei contributes less than 20% of Kab. Simalungun’s GDP. The dependent variable in the research is labor productivity, while the independent variable is the amount of labor, the level of labor education, the length of work and salary. This research used linear regression method to find the model for represent actual condition of productivity in two industrial area, then the equalization using dummy variable on labor education level variable. The initial hypothesis (Ho) in this research is that labor productivity in Bekasi Industrial Area will be higher than the productivity of labor in SEZ Sei Mangkei. The variable that supporting the accepted hypothesis are more labor, higher education, longer work and higher salary in Bekasi Industrial Area.

Keywords: labor, industrial city, linear regression, productivity

Procedia PDF Downloads 179

Authors: Johannes Atug, Stefan Braunreuther, Gunther Reinhart

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Volatile markets, as well as increasing global competition in manufacturing, lead to a high demand of flexible and agile production systems. These advanced production systems in turn conduct to high capital expenditure along with high investment risks. Developments in production regarding digitalization and cyber-physical systems result to a merger of informational- and operational technology. The approach of this paper is to benefit from this merger and present a framework of a production network with scalable production capacity and low capital expenditure by adaptation of the IT concept 'everything as a service' into the production environment.

Keywords: digital manufacturing system, everything as a service, reconfigurable production, value network

Procedia PDF Downloads 343

Authors: Amir Nazemi, Milad Ramezankhani, Marian Kӧrber, Abbas S. Milani

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The excellent strength to weight ratio of woven fabric composites, along with their high formability, is one of the primary design parameters defining their increased use in modern manufacturing processes, including those in aerospace and automotive. However, for emerging automated preform processes under the smart manufacturing paradigm, complex geometries of finished components continue to bring several challenges to the designers to cope with manufacturing defects on site. Wrinklinge. g. is a common defectoccurring during the forming process and handling of semi-finished textile composites. One of the main reasons for this defect is the weak bending stiffness of fibers in unconsolidated state, causing excessive relative motion between them. Further challenges are represented by the automated handling of large-area fiber blanks with specialized gripper systems. For fabric composites forming simulations, the finite element (FE)method is a longstanding tool usedfor prediction and mitigation of manufacturing defects. Such simulations are predominately meant, not only to predict the onset, growth, and shape of wrinkles but also to determine the best processing condition that can yield optimized positioning of the fibers upon forming (or robot handling in the automated processes case). However, the need for use of small-time steps via explicit FE codes, facing numerical instabilities, as well as large computational time, are among notable drawbacks of the current FEtools, hindering their extensive use as fast and yet efficient digital twins in industry. This paper presents a novel woven fabric simulation technique through the application of the material point method (MPM), which enables the use of much larger time steps, facing less numerical instabilities, hence the ability to run significantly faster and efficient simulationsfor fabric materials handling and forming processes. Therefore, this method has the ability to enhance the development of automated fiber handling and preform processes by calculating the physical interactions with the MPM fiber models and rigid tool components. This enables the designers to virtually develop, test, and optimize their processes based on either algorithmicor Machine Learning applications. As a preliminary case study, forming of a hemispherical plain weave is shown, and the results are compared to theFE simulations, as well as experiments.

Keywords: material point method, woven fabric composites, forming, material handling

Procedia PDF Downloads 181

Authors: Totok R. Biyanto, Arif T. Mardianto, M. Farid R. R., Luthfi Machmudi, kandi mulakasti

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The main objective of this research is optimizing the electrocoagulation process design as a post-treatment for biologically vinasse effluent process. The first principle model with three independent variables that affect the energy consumption of electrocoagulation process i.e. current density, electrode distance, and time of treatment process are chosen as optimized variables. The process condition parameters were determined with the value of pH, electrical conductivity, and temperature of vinasse about 6.5, 28.5 mS/cm, 52 oC, respectively. Aluminum was chosen as the electrode material of electrocoagulation process. Duelist algorithm was used as optimization technique due to its capability to reach a global optimum. The optimization results show that the optimal process can be reached in the conditions of current density of 2.9976 A/m2, electrode distance of 1.5 cm and electrolysis time of 119 min. The optimized energy consumption during process is 34.02 Wh.

Keywords: optimization, vinasse effluent, electrocoagulation, energy consumption

Procedia PDF Downloads 469

Authors: Atish Bagchi, Siva Chandrasekaran

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Background: According to World Bank national accounts data, the estimated global manufacturing value-added output in 2020 was 13.74 trillion USD. These manufacturing processes are monitored, modelled, and controlled by advanced, real-time, computer-based systems, e.g., Industrial IoT, PLC, SCADA, etc. These systems measure and manipulate a set of physical variables, e.g., temperature, pressure, etc. Despite the use of IoT, SCADA etc., in manufacturing, studies suggest that unplanned downtime leads to economic losses of approximately 864 billion USD each year. Therefore, real-time, accurate detection, classification and prediction of machine behaviour are needed to minimise financial losses. Although vast literature exists on time-series data processing using machine learning, the challenges faced by the industries that lead to unplanned downtimes are: The current algorithms do not efficiently handle the high-volume streaming data from industrial IoTsensors and were tested on static and simulated datasets. While the existing algorithms can detect significant 'point' outliers, most do not handle contextual outliers (e.g., values within normal range but happening at an unexpected time of day) or subtle changes in machine behaviour. Machines are revamped periodically as part of planned maintenance programmes, which change the assumptions on which original AI models were created and trained. Aim: This research study aims to deliver a Graph Neural Network(GNN)based hybrid forecasting model that interfaces with the real-time machine control systemand can detect, predict machine behaviour and behavioural changes (anomalies) in real-time. This research will help manufacturing industries and utilities, e.g., water, electricity etc., reduce unplanned downtimes and consequential financial losses. Method: The data stored within a process control system, e.g., Industrial-IoT, Data Historian, is generally sampled during data acquisition from the sensor (source) and whenpersistingin the Data Historian to optimise storage and query performance. The sampling may inadvertently discard values that might contain subtle aspects of behavioural changes in machines. This research proposed a hybrid forecasting and classification model which combines the expressive and extrapolation capability of GNN enhanced with the estimates of entropy and spectral changes in the sampled data and additional temporal contexts to reconstruct the likely temporal trajectory of machine behavioural changes. The proposed real-time model belongs to the Deep Learning category of machine learning and interfaces with the sensors directly or through 'Process Data Historian', SCADA etc., to perform forecasting and classification tasks. Results: The model was interfaced with a Data Historianholding time-series data from 4flow sensors within a water treatment plantfor45 days. The recorded sampling interval for a sensor varied from 10 sec to 30 min. Approximately 65% of the available data was used for training the model, 20% for validation, and the rest for testing. The model identified the anomalies within the water treatment plant and predicted the plant's performance. These results were compared with the data reported by the plant SCADA-Historian system and the official data reported by the plant authorities. The model's accuracy was much higher (20%) than that reported by the SCADA-Historian system and matched the validated results declared by the plant auditors. Conclusions: The research demonstrates that a hybrid GNN based approach enhanced with entropy calculation and spectral information can effectively detect and predict a machine's behavioural changes. The model can interface with a plant's 'process control system' in real-time to perform forecasting and classification tasks to aid the asset management engineers to operate their machines more efficiently and reduce unplanned downtimes. A series of trialsare planned for this model in the future in other manufacturing industries.

Keywords: GNN, Entropy, anomaly detection, industrial time-series, AI, IoT, Industry 4.0, Machine Learning

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Authors: Johana Jaramillo, Robin Kalfat, Dmitriy A. Dikin

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The cement production process is one of the major sources of carbon dioxide (CO₂), a potent greenhouse gas. Indeed, as a result of its cement manufacturing process, concrete contributes approximately 8% of global greenhouse gas emissions. In addition to environmental concerns, concrete also has a low tensile and ductility strength, which can lead to cracks. Graphene nanoplatelets (GNPs) have proven to be an eco-friendly solution for improving the mechanical and durability properties of concrete. The current research investigates the effects of preparing concrete enhanced with GNPs by using different wet dispersions techniques and mixing methods on its mechanical properties. Concrete specimens were prepared with 0.00 wt%, 0.10 wt%, 0.20 wt%, 0.30 wt% and wt% GNPs. Compressive and flexural strength of concrete at age 7 days were determined. The results showed that the maximum improvement in mechanical properties was observed when GNPs content was 0.20 wt%. The compressive and flexural were improved by up to 17.5% and 8.6%, respectively. When GNP dispersions were prepared by the combination of a drill and an ultrasonic probe, mechanical properties experienced maximum improvement.

Keywords: concrete, dispersion techniques, graphene nanoplatelets, mechanical properties, mixing methods

Procedia PDF Downloads 124

Authors: Haftu Hailu Berhe, Hailekiros Sibhato Gebremichael, Kinfe Tsegay Beyene, Haileselassie Mehari

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The purpose of the study is to develop and validate integrated literature-based JIT, TQM, TPM, SCM and LSS framework through a combination of the PDCA cycle and DMAIC methodology. The study adopted a mixed research approach. Accordingly, the qualitative study employed to develop the framework is based on identifying the uniqueness and common practices of JIT, TQM, TPM, SCM and LSS initiatives, the existing practice of the integration, identifying the existing gaps in the framework and practices, developing new integrated JIT, TQM, TPM, SCM and LSS practice framework. Previous very few studies of the uniqueness and common practices of the five initiatives are preserved. Whereas the quantitative study working to validate the framework is based on empirical analysis of the self-administered questionnaire using a statistical package for social science. A combination of the PDCA cycle and DMAIC methodology stand integrated CI framework is developed. The proposed framework is constructed as a project-based framework with five detailed implementation phases. Besides, the empirical analysis demonstrated that the proposed framework is valuable if adopted and implemented correctly. So far, there is no study proposed & validated the integrated CI framework within the scope of the study. Therefore, this is the earliest study that proposed and validated the framework for manufacturing industries. The proposed framework is applicable to manufacturing industries and can assist in achieving competitive advantages when the manufacturing industries, institutions and government offer unconditional efforts in implementing the full contents of the framework.

Keywords: integrated continuous improvement framework, just in time, total quality management, total productive maintenance, supply chain management, lean six sigma

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Authors: R. Knizek, D. Karhankova

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The production of nanofibers and the machinery for their production is a current issue. The pioneer, in the industrial production of nanofibers, is the machinery with the sales descriptions Nanospider^TM from the company Elmarco, which came into being in 2008. Most of the production facilities, like Nanospider^TM, use electrospinning. There are also other methods of industrial production of nanofibers, such as the centrifugal spinning process, which is used by FibeRio Technology Corporation. However, each method and machine has its advantages, but also disadvantages and that is the reason why a new machine called as Nanomachine, which eliminates the disadvantages of other production facilities producing nanofibers, has been developed.

Keywords: nanomachine, nanospider, spinning slat, electrospinning

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Authors: Mohita Gangwar Sharma

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Different factors are compelling manufacturers to move towards the phenomenon of servitization i.e. when firms go beyond giving support to the customers in operating the equipment. The challenges that are being faced in this transition by the manufacturing firms from being a product provider to a product- service provider are multipronged. Product-Service Systems (PSS) lies in between the pure-product and pure-service continuum. Through this study, we wish to understand the dimensions of ‘PSS-quality’. We draw upon the quality literature for both the product and services and through an expert survey for a specific transportation sector using analytical hierarchical process (AHP) derive a conceptual model that can be used as a comprehensive measurement tool for PSS offerings.

Keywords: servitisation, quality, product-service system, AHP

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Authors: Georgios Koronis, Arlindo Silva

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This study seeks to understand the mechanical behavior of a natural fiber reinforced composite (epoxy/flax) in more depth, utilizing both experimental and numerical methods. It is attempted to identify relationships between the design parameters and the product performance, understand the effect of noise factors and reduce process variations. Optimization of the mechanical performance of manufactured goods has recently been implemented by numerous studies for green composites. However, these studies are limited and have explored in principal mass production processes. It is expected here to discover knowledge about composite’s manufacturing that can be used to design artifacts that are of low batch and tailored to niche markets. The goal is to reach greater consistency in the performance and further understand which factors play significant roles in obtaining the best mechanical performance. A prediction of response function (in various operating conditions) of the process is modeled by the DoE. Normally, a full factorial designed experiment is required and consists of all possible combinations of levels for all factors. An analytical assessment is possible though with just a fraction of the full factorial experiment. The outline of the research approach will comprise of evaluating the influence that these variables have and how they affect the composite mechanical behavior. The coupons will be fabricated by the vacuum infusion process defined by three process parameters: flow rate, injection point position and fiber treatment. Each process parameter is studied at 2-levels along with their interactions. Moreover, the tensile and flexural properties will be obtained through mechanical testing to discover the key process parameters. In this setting, an experimental phase will be followed in which a number of fabricated coupons will be tested to allow for a validation of the design of the experiment’s setup. Finally, the results are validated by performing the optimum set of in a final set of experiments as indicated by the DoE. It is expected that after a good agreement between the predicted and the verification experimental values, the optimal processing parameter of the biocomposite lamina will be effectively determined.

Keywords: design of experiments, flax fabrics, mechanical performance, natural fiber reinforced composites

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Authors: Khaled Al-Badani, James Ren, Lisa Li, David Allanson

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Droplet formation is an important process in many engineering systems and manufacturing procedures, which includes welding, biotechnologies, 3D printing, biochemical, biomedical fields and many more. The volume and the characteristics of droplet formation are generally depended on various material properties, microfluidics and fluid mechanics considerations. Hence, a detailed investigation of this process, with the aid of numerical computational tools, are essential for future design optimization and process controls of many engineering systems. This will also improve the understanding of changes in the properties and the structures of materials, during the formation of the droplet, which is important for new material developments to achieve different functions, pending the requirements of the application. For example, the shape of the formed droplet is critical for the function of some final products, such as the welding nugget during Capacitor Discharge Welding process, or PLA 3D printing, etc. Although, most academic journals on droplet formation, focused on issued with material transfer rate, surface tension and residual stresses, the general emphasis on the characteristics of droplet shape has been overlooked. The proposed work for this project will examine theoretical methodologies, experimental techniques, and numerical modelling, using ANSYS FLUENT, to critically analyse and highlight optimization methods regarding the formation of pendant droplet. The project will also compare results from published data with experimental and numerical work, concerning the effects of key material parameters on the droplet shape. These effects include changes in heating/cooling rates, solidification/melting progression and separation/break-up times. From these tests, a set of objectives is prepared, with an intention of improving quality, stability and productivity in modelling metal welding and 3D printing.

Keywords: computer modelling, droplet formation, material distortion, materials forming, welding

Procedia PDF Downloads 286

Authors: Napatsorn Suput-Anyaporn

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This paper aimed to investigate multilateral relationships across the factors which included labor shortage, trade union, turnover rate of employee, labor law and regulation, and effectiveness of foreign worker administration in the scope of foreign workers in the industrial manufacturing sector of Thailand. The research employed both quantitative and qualitative approaches, in which foreign workers from Myanmar, Laos and Cambodia in the industrial manufacturing sector in selected areas of Thailand were sampled for the quantitative data collection, and persons in the chief executive management and the supervisor levels, and persons in the academic area in relation with foreign workers were selected as the sample for the qualitative data collection method. Thus, a questionnaire, in-depth interview and focus group were utilized as tools in this research paper. The discussion placed an emphasis on the fact that Thailand should design more effective law and regulations for the foreign workers administration and management in response to preparing for the coming ASEAN Economic Community with the declaration of the free- flow labor movement policy.

Keywords: industrial manufacturing sector, labor law and regulation, labor shortage, migrant worker, trade union, turnover rate of employee

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Authors: Emmanuel Ogundimu, Esther Akinlabi, Mutiu Erinosho

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Welding is described as the process of joining metals so that bonding can be created as a result of inter-atomic penetration. This study investigated the influence of heat input on the efficiency of the welded joints of 304 stainless steel. Three welds joint were made from two similar 304 stainless steel plates of thickness 6 mm. The tensile results obtained showed that the maximum average tensile strength of 672 MPa is possessed by the sample A1 with low heat input. It was discovered that the tensile strength, % elongation and weld joint efficiency decreased with the increase in heat input into the weld. The average % elongation for the entire samples ranged from 28.4% to 36.5%. Sample A1 had the highest joint efficiency of 94.5%. However, the optimum welding current of 190 for TIG- MIG hybrid welding of type-304 austenite stainless steel can be recommended for advanced technological applications such as aircraft manufacturing, nuclear industry, automobile industry, and processing industry.

Keywords: microhardness, microstructure, tensile, MIG welding, process, tensile, shear stress TIG welding, TIG-MIG welding

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Authors: Amin Nazerzadeh, Afsaneh Nouri Houshyar , Azadeh Noori Hoshyar

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With the rapid growing of information technology, the industry and manufacturing systems are becoming more automated. Therefore, achieving the highly accurate automatic systems with reliable security is becoming more critical. Biometrics that refers to identifying individual based on physiological or behavioral traits are unique identifiers provide high reliability and security in different industrial systems. As biometric cannot easily be transferred between individuals or copied, it has been receiving extensive attention. Due to the importance of security applications, this paper provides an overview on biometrics and discuss about background, types and applications of biometric as an effective tool for the industrial applications.

Keywords: Industial and manufacturing applications, intelligence and security, information technology, recognition; security technology; biometrics

Procedia PDF Downloads 155

Authors: Mohammad Rostami Mehr, Seyed Arya Mir Rashed, Arndt Lueder, Magdalena Missler-Behr

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This paper represents the conception that complex problems do not necessarily need a similar complex solution in order to cope with the complexity. Furthermore, a simple solution based on established methods can provide a sufficient way to deal with the complexity. To verify this conception, the presented paper focuses on the field of change management as a part of the new product development process in the automotive sector. In this field, dealing with increasing complexity is essential, while only non-flexible rigid processes that are not designed to handle complexity are available. The basic methodology of this paper can be divided into four main sections: 1) analyzing the complexity of the change management, 2) literature review in order to identify potential solutions and methods, 3) capturing and implementing expertise of experts from the change management field of an automobile manufacturing company and 4) systematical comparison of the identified methods from literature and connecting these with defined requirements of the complexity of the change management in order to develop a solution. As a practical outcome, this paper provides a method to capture the complexity of engineering changes (EC) and includes it within the EC evaluation process, following case-related process guidance to cope with the complexity. Furthermore, this approach supports the conception that dealing with complexity is possible while utilizing rather simple and established methods by combining them into a powerful tool.

Keywords: complexity management, new product development, engineering change management, flexibility

Procedia PDF Downloads 197

Authors: James Newman

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Process mining is an emerging technology that looks to serialize enterprise data in time series data. It has been used by many companies and has been the subject of a variety of research papers. However, the majority of current efforts have looked at how to best create process mining from standard relational databases. This paper is the first pass at outlining a database custom-built for the minimal viable product of process mining. We present Block Miner, a blockchain protocol to store process mining data across a distributed network. We demonstrate the feasibility of storing process mining data on the blockchain. We present a proof of concept and show how the intersection of these two technologies helps to solve a variety of issues, including but not limited to ransomware attacks, tax documentation, and conflict resolution.

Keywords: blockchain, process mining, memory optimization, protocol

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Authors: Sedat Yayla, Azhin Abdullah

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In the process of constructing hydroelectric power plants, the Pelton turbine, which is characterized by its simple manufacturing and construction, is performed in high head and low water flow. Parameters of the turbine have to be comprised in the designing process for obtaining hydraulic turbine with the highest efficiency during different operating conditions. The present investigation applied three-dimensional computational fluid dynamics (CFD). In addition, the bucket of Pelton turbine models with different splitter angle and inlet velocity values were examined for determining the force and visualizing the flow pattern on the bucket. The study utilized two diverse bucket models at various inlet velocities (20, 25, 30,35and 40m/s) and four different splitter angles (55, 75,90and 115 degree) for finding out the impacts of every single parameter on the effective force on the bucket. The acquired outcomes revealed that there is a linear relationship between force and inlet velocity on the bucket. Furthermore, the results also uncovered that the relationship between splitter angle and force on the bucket is linear until 90 degree.

Keywords: bucket design, computational fluid dynamics (CFD), free surface flow, two-phase flow, volume of fluid (VOF)

Procedia PDF Downloads 271

Authors: Seung-Lock Seo

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This work presents a data-mining empirical monitoring scheme for industrial processes with partially unbalanced data. Measurement data of good operations are relatively easy to gather, but in unusual special events or faults it is generally difficult to collect process information or almost impossible to analyze some noisy data of industrial processes. At this time some noise filtering techniques can be used to enhance process monitoring performance in a real-time basis. In addition, pre-processing of raw process data is helpful to eliminate unwanted variation of industrial process data. In this work, the performance of various monitoring schemes was tested and demonstrated for discrete batch process data. It showed that the monitoring performance was improved significantly in terms of monitoring success rate of given process faults.

Keywords: data mining, process data, monitoring, safety, industrial processes

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Authors: Egoitz Aldanondo, Ekaitz Arruti, Amaia Iturrioz, Ivan Huarte, Fidel Zubiri

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Manufacturing aeronautic structures joining extruded profiles or stringers to sheets or skins of aluminium is a typical manufacturing procedure in aeronautic structures. Although riveting is the conventional manufacturing technology to produce such joints, the Friction Stir Welding (FSW) and Laser Beam Welding (LBW) technologies have also demonstrated their potential for this kind of applications. Therefore, FSW and LBW technologies have the potential to continue their development as manufacturing processes for aeronautic structures showing benefits such as time-saving, light-weighting and overall cost reduction. In addition to that, new aluminium-lithium based alloy developments represent great opportunities for advanced aeronautic structure manufacturing with potential benefits such as lightweight construction or improved corrosion resistance. This work presents the main approaches by FSW and LBW to develop those technologies to produce stiffened panel structures such as fuselage by stringer-skin joints and using innovative aluminium-lithium alloys. Initial welding tests were performed in AA2198-T3S aluminium alloys for LBW technology and with AA2198-T851 for FSW. Later tests for both FSW and LBW have been carried out using AA2099-T83 alloy extrusions as stringers and AA2060-T8E30 as skin materials. The weld quality and properties have been examined by metallographic analysis and mechanical testing, including shear tensile tests and pull-out tests. The analysis of the results have shown the relationships between processing conditions, micro-macrostructural properties and the mechanical strength of the welded joints. The effects produced in the different alloys investigated have been observed and particular weld formation mechanics have been studied for each material and welding technology. Therefore, relationships between welding conditions and the obtained weld properties for each material combination and welding technology will be discussed in this presentation.

Keywords: AA2060-T8E30, AA2099-T83, AA2198-T3S, AA2198-T851, friction stir welding, laser beam welding

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Authors: Husam Kaid, Abdulrahman Al-Ahmari, Zhiwu Li

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This paper develops a robust deadlock control technique for shared and unreliable resources in automated manufacturing systems (AMSs) based on structural analysis and colored Petri nets, which consists of three steps. The first step involves using strict minimal siphon control to create a live (deadlock-free) system that does not consider resource failure. The second step uses an approach based on colored Petri net, in which all monitors designed in the first step are merged into a single monitor. The third step addresses the deadlock control problems caused by resource failures. For all resource failures in the Petri net model a common recovery subnet based on colored petri net is proposed. The common recovery subnet is added to the obtained system at the second step to make the system reliable. The proposed approach is evaluated using an AMS from the literature. The results show that the proposed approach can be applied to an unreliable complex Petri net model, has a simpler structure and less computational complexity, and can obtain one common recovery subnet to model all resource failures.

Keywords: automated manufacturing system, colored Petri net, deadlocks, siphon

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Authors: Gerrit Ter Haar, Thorsten Becker, Deborah Blaine

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The Additive Manufacturing (AM) process of Selective Laser Melting (SLM) has seen an exponential growth in sales and development in the past fifteen years. Whereas the capability of SLM was initially limited to rapid prototyping, progress in research and development (R&D) has allowed SLM to be capable of fully functional parts. This technology is still at a primitive stage and technical knowledge of the vast number of variables influencing final part quality is limited. Ongoing research and development of the sensitive printing process and post processes is of utmost importance in order to qualify SLM parts to meet international standards. Quality concerns in Ti-6Al-4V manufactured through SLM has been identified, which include: high residual stresses, part porosity, low ductility and anisotropic mechanical properties. Whereas significant quality improvements have been made through optimising printing parameters, research indicates as-produced part ductility to be a major limiting factor when compared to its wrought counterpart. This study aims at achieving an in-depth understanding of the underlining links between SLM produced Ti-6Al-4V microstructure and its mechanical properties. Knowledge of microstructural transformation kinetics of Ti-6Al-4V allows for the optimisation of post-process heat treatments thereby achieving the required process route to manufacture high quality SLM produced Ti-6Al-4V parts. Experimental methods used to evaluate the kinematics of microstructural transformation of SLM Ti-6Al-4V are: optical microscopy and electron backscatter diffraction. Results show that a low-temperature heat treatment is capable of transforming the as-produced, martensitic microstructure into a duel-phase microstructure exhibiting both a high strength and improved ductility. Furthermore, isotropy of mechanical properties can be achieved through certain annealing routes. Mechanical properties identical to that of wrought Ti-6Al-4V can, therefore, be achieved through an optimised process route.

Keywords: EBSD analysis, heat treatments, microstructural characterisation, selective laser melting, tensile behaviour, Ti-6Al-4V

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Authors: Payal Patel

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Textile machinery is one of the fastest evolving areas which has an application of mechanical engineering. The modular approach towards the processing right from the stage of cotton to the fabric, allows us to observe the result of each process on its input. Cost and space being the major constraints. The flyer is a component of roving machine, which is used as a part of spinning process. In the present work using the application of Hyper Works, the flyer arm has been modified which saves the material used for manufacturing the flyer. The size optimization of the flyer is carried out with the objective of reduction in weight under the constraints of standard operating conditions. The new design of the flyer is proposed and validated using the module of HyperWorks which is equally strong, but light weighted compared to the existing design. Dynamic balancing of the optimized model is carried out to align a principal inertia axis with the geometric axis of rotation. For the balanced geometry of flyer, air resistance is obtained theoretically and with Gambit and Fluent. Static analysis of the balanced geometry has been done to verify the constraint of operating condition. Comparison of weight, deflection, and factor of safety has been made for different aluminum alloys.

Keywords: flyer, size optimization, textile, weight

Procedia PDF Downloads 215

Authors: Udeh Nneka Evelyn

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The shortcoming of traditional costing system in terms of validity, accuracy, consistency, and Relevance increased the need for modern management accounting system. Activity –Based Costing (ABC) can be used as a modern tool for planning, Control and decision making for management. Past studies on ABC system have focused on manufacturing firms thereby making the studies on service firms scanty to some extent. This paper reviewed the application and relevance of activity-based costing technique in service oriented business organizations by employing a qualitative research method which relied heavily on literature review of past and current relevant articles focusing on ABC. Findings suggest that ABC is not only appropriate for use in a manufacturing environment; it is also most appropriate for service organizations such as financial institutions, the healthcare industry and government organization. In fact, some banking and financial institutions have been applying the concept for years under other names. One of them is unit costing, which is used to calculate the cost of banking services by determining the cost and consumption of each unit of output of functions required to deliver the service. ABC in very basic terms may provide very good payback for businesses. Some of the benefits that relate directly to the financial services industry are: identification the most profitable customers: more accurate product and service pricing: increase product profitability: Well organized process costs.

Keywords: business, costing, organizations, planning, techniques

Procedia PDF Downloads 240

Authors: M. Ndeley

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Now our days, Almost all manufacturing facilities need to use production planning and scheduling systems to increase productivity and to reduce production costs. Real-life production operations are subject to a large number of unexpected disruptions that may invalidate the original schedules. In these cases, rescheduling is essential to minimize the impact on the performance of the system. In this work we consider flow shop layouts that have seldom been studied in the rescheduling literature. We generate and employ three types of disruption that interrupt the original schedules simultaneously. We develop rescheduling algorithms to finally accomplish the twofold objective of establishing a standard framework on the one hand; and proposing rescheduling methods that seek a good trade-off between schedule quality and stability on the other.

Keywords: flow shop scheduling, uncertainty, rescheduling, stability

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Authors: Dennis Kreutzer, Sarah Müller-Abdelrazeq, Ingrid Isenhardt

Abstract:

Resource scarcity, energy transition and the planned climate neutrality pose enormous challenges for manufacturing companies. In order to achieve these goals and a holistic sustainable development, the European Union has listed the circular economy as part of the Circular Economy Action Plan. In addition to a reduction in resource consumption, reduced emissions of greenhouse gases and a reduced volume of waste, the principles of the circular economy also offer enormous economic potential for companies, such as the generation of new circular business models. However, many manufacturing companies, especially small and medium-sized enterprises, do not have the necessary capacity to plan their transformation. They need support and strategies on the path to circular transformation, because this change affects not only production but also the entire company. Maturity models offer an approach, as they enable companies to determine the current status of their transformation processes. In addition, companies can use the models to identify transformation strategies and thus promote the transformation process. While maturity models are established in other areas, e.g. IT or project management, only a few circular economy maturity models can be found in the scientific literature. The aim of this paper is to analyse the identified maturity models of the circular economy through a systematic literature review (SLR) and, besides other aspects, to check their completeness as well as their quality. Since the terms "maturity model" and "readiness model" are often used to assess the transformation process, this paper considers both types of models to provide a more comprehensive result. For this purpose, circular economy maturity models at the company (micro) level were identified from the literature, compared, and analysed with regard to their theoretical and methodological structure. A specific focus was placed, on the one hand, on the analysis of the business units considered in the respective models and, on the other hand, on the underlying metrics and indicators in order to determine the individual maturity level of the entire company. The results of the literature review show, for instance, a significant difference in the holism of their assessment framework. Only a few models include the entire company with supporting areas outside the value-creating core process, e.g. strategy and vision. Additionally, there are large differences in the number and type of indicators as well as their metrics. For example, most models often use subjective indicators and very few objective indicators in their surveys. It was also found that there are rarely well-founded thresholds between the levels. Based on the generated results, concrete ideas and proposals for a research agenda in the field of circular economy maturity models are made.

Keywords: maturity model, circular economy, transformation, metric, assessment

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Authors: Won Jung

Abstract:

In automotive, propeller shaft is the device for transferring power from engine to axle via transmission, and the slip yoke is one of the main parts in the component. Since the propeller shafts are subject to torsion and shear stress, they need to be strong enough to bear the stress. The purpose of this research is to improve the productivity of slip yoke for automotive propeller shaft. We present how to redesign the component that currently manufactured as a forged single body type. The research was focused on not only reducing processing time but insuring durability of the component simultaneously.

Keywords: automotive, propeller shaft, productivity, durability, slip yoke

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Authors: Ashfaq Khan, Aftab Khan, Mushtaq Khan, Sarem Sattar, Mohammad A Sheikh, Lin Li

Abstract:

Chip removal processes are one of key processes of the manufacturing industry where chip removal is conducted by tool inserts of exceptionally hard materials. Tungsten carbide has been extensively used as tool insert for machining processes involving chip removal processes. These hard materials are generally fabricated by single step sintering process as further modification after fabrication in these materials cannot be done easily. Advances in tool surface modification have revealed that advantages such as improved tribological properties and extended tool life can be harnessed from the same tool by texturing the tool rake surface. Moreover, it has been observed that the shape and location of the texture also influences the behavior. Although texturing offers plentiful advantages the challenge lies in the generation of textures on the tool surface. Extremely hard material such as diamond is required to process tungsten carbide. Laser is unique processing tool that does not have a physical contact with the material and thus does not wear. In this research the potential of utilizing laser for texturing of tungsten carbide to develop custom features would be studied. A parametric study of texturing of Tungsten Carbide with a femtosecond laser would be conducted to investigate the process parameters and establish the feasible processing window. The effect of fluence, scan speed and number of repetition would be viewed in detail. Moreover, the mechanism for the generation of features would also be reviewed.

Keywords: laser, texturing, femtosecond, tungsten carbide

Procedia PDF Downloads 658

Authors: Maryam Ziaee

Abstract:

This research proposes a new approach and provides an opportunity for manufacturing companies to produce large amounts of products that meet their prospective customers’ tastes, needs, and expectations and simultaneously enable manufacturers to increase their profit. Mass customization is the production of products or services to meet each individual customer’s desires to the greatest possible extent in high quantities and at reasonable prices. This process takes place at different levels such as the customization of goods’ design, assembly, sale, and delivery status, and classifies in several categories. The main focus of this study is on one class of mass customization, called optional customization, in which companies try to provide their customers with as many options as possible to customize their products. These options could range from the design phase to the manufacturing phase, or even methods of delivery. Mass customization values customers’ tastes, but it is only one side of clients’ satisfaction; on the other side is companies’ fast responsiveness delivery. It brings the concept of agility, which is the ability of a company to respond rapidly to changes in volatile markets in terms of volume and variety. Indeed, mass customization is not effectively feasible without integrating the concept of agility. To gain the customers’ satisfaction, the companies need to be quick in responding to their customers’ demands, thus highlighting the significance of agility. This research offers a different method that successfully integrates mass customization and fast production in manufacturing industries. This research is built upon the hypothesis that the success key to being agile in mass customization is to forecast demand, cooperate with suppliers, and control inventory. Therefore, the significance of the supply chain (SC) is more pertinent when it comes to this stage. Since SC behavior is dynamic and its behavior changes constantly, companies have to apply one of the predicting techniques to identify the changes associated with SC behavior to be able to respond properly to any unwelcome events. System dynamics utilized in this research is a simulation approach to provide a mathematical model among different variables to understand, control, and forecast SC behavior. The final stage is delayed differentiation, the production strategy considered in this research. In this approach, the main platform of products is produced and stocked and when the company receives an order from a customer, a specific customized feature is assigned to this platform and the customized products will be created. The main research question is to what extent applying system dynamics for the prediction of SC behavior improves the agility of mass customization. This research is built upon a qualitative approach to bring about richer, deeper, and more revealing results. The data is collected through interviews and is analyzed through NVivo software. This proposed model offers numerous benefits such as reduction in the number of product inventories and their storage costs, improvement in the resilience of companies’ responses to their clients’ needs and tastes, the increase of profits, and the optimization of productivity with the minimum level of lost sales.

Keywords: agility, manufacturing, resilience, supply chain

Procedia PDF Downloads 90