Cost modelling of rapid manufacturing based mass customisation system for fabrication of custom foot orthoses

PhD ThesisSolid freeform fabrication (SFF) or Additive manufacturing (AM) techniques have emerged in recent years as advanced manufacturing techniques. These techniques have demonstrated advantages particularly in situations where the demands for unique geometrical structured customer-specific products are high and the time to market is very short. Applications of these techniques in the medical sector in combination with the latest medical digital imaging technologies are growing quickly. The techniques have inherent advantages of compatibility with the output information of medical digitising techniques. Foot orthoses are medical devices used as shoe inserts in the treatment of foot disorders, injuries and diseases such as diabetes, rheumatoid arthritis, congenital defects and other foot related injuries. Currently custom foot orthoses are fabricated through manufacturing techniques which involve costly and based on lengthy trial and error manufacturing process. These techniques have limitations in terms of fabricating required geometries and incorporating complex design features in the custom-made orthoses. The novelty of this research is to explore the commercial scale application of rapid manufacturing techniques and to assess a rapid manufacturing based design and fabrication system for production of custom foot orthoses. The developed system is aimed at delivering the custom made orthoses at mass scale with improved fit, consistency, accuracy and increased product quality. The traditional design and fabrication process for production of custom foot orthoses was investigated and modelled with IDEF0 modelling methodology. The developed IDEF0 model was re-modelled and then the rapid manufacturing approach was integrated in the design and fabrication process. The main functions of foot geometry capture, orthoses design and manufacture of orthoses were modelled and evaluated individually with respect to time and cost and quality of the final product. Different well-established rapid manufacturing techniques were integrated in the current design and fabrication process. The results showed that the techniques have significant impacts on the overall design and fabrication process in terms of increased process efficiency, low lead-time, increased productivity and improved quality of the final product. An orthosis model was fabricated on an experimental basis using different well established rapid manufacturing techniques. The techniques were separately investigated and analysed in terms of orthoses fabrication cost and build time. The cost and lead-time in different techniques were modelled, analysed and evaluated for evaluation of commercial scale applications. The analysis and evaluation of the cost and lead-time modelled for different rapid manufacturing techniques showed that selective laser sintering technique is the better option for integrating the technique in fabrication of custom foot orthoses and that it has the potential to compete with conventional techniques

Thermal Measurements based on Image Processing for In-Situ Monitoring of 3D Fused Filament Fabrication (FFF).

Nowadays new applications based on the 3D printing technique demand increasingly strict product quality requirements. The in-situ monitoring of variables associated with the manufacturing process through the application of different techniques could help to evaluate the process and ultimately to ensure product quality. In this regard, the acquisition and evaluation of variables and indexes derived from thermographic analysis during the process are key for an early defect detection and can contribute to quality estimation. In this work, a new methodology is proposed for the monitoring and analysis of the additive manufacturing process based on the processing of thermographic images from an LWIR (Long Wave Infrared) camera. The methodology and the suitability of the variables and indexes extracted during the monitoring of the manufacturing process are discussed for the case of a 3D fused filament fabrication of polymers.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Exergy Analysis as a Developed Concept of Energy Efficiency Optimized Processes: The Case of Thermal Spray Processes

AbstractGiven the global economic growth and the rapid manufacturing development, the energy and resource efficiency will become an increasingly competitive factor and scope for the companies in the road of sustainability. Among energy efficiency optimization approaches, thermodynamics methodologies contribute toward the improvement of energy efficiency in manufacturing processes. Besides energy balance, exergy has been recently considered as a practical thermodynamics method for system's energy evaluation. From the exergy analysis, merging both exergy efficiency and exergy destruction highlights the energy inefficiencies within a system and provides useful information to the managers and decision makers for prioritizing the improvement potentials. Exergy analysis is generally an applicable method for the comparison of the alternative processes for a given purpose.In this study, thermal spray process techniques (APS, SPS, HVOF, HVSFS) as energy intensive manufacturing processes are analyzed and compared on the basis of exergy and energy analysis methods. For a comprehensive evaluation, energy efficiency as well as exergy efficiency and exergy destruction are proposed as the indicators.This work concludes with a discussion of the advantages of the exergy analysis method in comparison with a conventional energy efficiency evaluation by validation of the results for the case of thermal spray processes

Process Control Parameters Evaluation Using Discrete Event Simulation for Business Process Optimization

The quest for manufacturing process improvement and higher levels of customer satisfaction mandates that organizations must be equipped with advanced tools and techniques in order to respond towards ever changing internal and external customer demands by maintaining the optimal process performance, lower cost and higher profit levels. A manufacturing process can be defined as a collection of activities designed to produce a specific output for a particular customer or market. To achieve internal and external objectives, significant process parameters must be identified and evaluated to optimize the process performance. This even becomes more important to deal with fierce competition and ever changing customer demands. This paper illustrates an integrated approach using design of experiments techniques and discrete event simulation (Simul8) to understand and optimize the system dynamic based on operational control parameter evaluation and their boundary conditions. Further, the proposed model is validated using a real world manufacturing process case study to optimize the manufacturing process performance. Discrete event simulation tool is used to mimic the real world scenario, which provides a flexible and powerful way to comprehensively understand the manufacturing process variations and allows controlled 'What-If´ analysis based on design of experiments approach. Finally, this paper discusses the potential applications of the proposed methodology in the cable industry in order to optimize the cable manufacturing process by regulating the operational control parameters such as dealing with various product configurations with different equipment settings, different product flows and work in process (WIP) space limitations

Prospects for the development of advanced grain processing in Russia

Purpose: The article is devoted to the identifying and evaluating promising areas of advanced grain and legumes processing development as a strategically important area for import substitution and food security of the agribusiness complex. Methodology/Approach: To achieve this goal, it is necessary to solve the following tasks: the analysis of advanced grain and legumes processing products; the evaluation of the current Russian market for advanced grain processing products; the identification of promising products and directions of the advanced grain processing industry development. Findings: According to the analysis in this article, this industry is in its infancy, despite the fact that in most developed countries of the world, advanced grain processing is widely elaborated. The key reasons for the Russia's lag there involve the lack of domestic techniques and highly qualified specialists in this field. Processing grain into flour, starches, glucose syrups, biofuels and organic acids makes possible manufacturing plastic and other products. To realize the Russia's potential in manufacturing high-value-added agricultural products, it is necessary to provide state support for investment projects for wheat deep processing through preferential lending and taxation, and co-financing of projects. The strategic goal of the Russian agribusiness in the medium and long term should be changing the structure of manufacturing and export in order to export finished products, but not raw materials. Practical implications: The results of this research could be introduced in the process of strategic planning of the agribusiness development and import substitution policy in Russia. Originality/Value: The key contribution of this study lies in the findings of the advanced grain processing industries’ analysis in Russia with the regional aspects taken into account.peer-reviewe

An integrated value-derivative model for the steel industry to evaluate and optimize the impact of operational strategies using total enterprise performance indicators

The purpose of this research was to develop a structured evaluation and optimization methodology for a prototype Value Chain Analysis model created by the Oak Ridge National Laboratory to identify and select new operational strategies/technologies for steel manufacturing plants in order to enhance their performance. The research’s major objectives were (a) to develop an enterprise mathematical model that describes the steel manufacturing process in terms of performance indicators, that adequately explains the marginal changes in outputs that occur per unit changes in inputs at the process step level, and that further illustrates how each process chains together in the production sequence; (b) to develop enterprise mathematical programming models for a number of optimization approaches to search for optimal or pareto-optimal values of the process performance indicators given a set of parameters; and (c) to develop methods to numerically solve, through a mix of heuristic and optimization techniques, the mathematical programming problems to optimize the manufacturing process’ performance in order to achieve the maximum leveraged benefits for the entire enterprise

Performance of a novel wafer scale CMOS active pixel sensor for bio-medical imaging

Recently CMOS Active Pixels Sensors (APSs) have become a valuable alternative to amorphous Silicon and Selenium Flat Panel Imagers (FPIs) in bio-medical imaging applications. CMOS APSs can now be scaled up to the standard 20 cm diameter wafer size by means of a reticle stitching block process. However despite wafer scale CMOS APS being monolithic, sources of non-uniformity of response and regional variations can persist representing a significant challenge for wafer scale sensor response. Non-uniformity of stitched sensors can arise from a number of factors related to the manufacturing process, including variation of amplification, variation between readout components, wafer defects and process variations across the wafer due to manufacturing processes. This paper reports on an investigation into the spatial non-uniformity and regional variations of a wafer scale stitched CMOS APS. For the first time a per-pixel analysis of the electro-optical performance of a wafer CMOS APS is presented, to address inhomogeneity issues arising from the stitching techniques used to manufacture wafer scale sensors. A complete model of the signal generation in the pixel array has been provided and proved capable of accounting for noise and gain variations across the pixel array. This novel analysis leads to readout noise and conversion gain being evaluated at pixel level, stitching block level and in regions of interest, resulting in a coefficient of variation ≤ 1.9%. The uniformity of the image quality performance has been further investigated in a typical X-ray application, i.e. mammography, showing a uniformity in terms of CNR among the highest when compared with mammography detectors commonly used in clinical practise. Finally, in order to compare the detection capability of this novel APS with the currently used technology (i.e. FPIs), theoretical evaluation of the Detection Quantum Efficiency (DQE) at zero-frequency has been performed, resulting in a higher DQE for this detector compared to FPIs. Optical characterization, X-ray contrast measurements and theoretical DQE evaluation suggest that a trade off can be found between the need of a large imaging area and the requirement of a uniform imaging performance, making the DynAMITe large area CMOS APS suitable for a range of bio-medical applications

Investment justification of information systems: A focus on the evaluation of MRPII

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.A review of the normative literature, in the field of Information Technology (IT)/ Information System (IS) justification, examines how organisations evaluate their investments in Manufacturing Resource Planning (MRPII). This is achieved through investigating the issues surrounding capital budgeting, with a particular focus on investment appraisal. In doing so, a novel taxonomy of generic appraisal techniques is proposed. This taxonomy identifies a number of methods for appraising MRPII investments, and through describing these techniques, a classification is offered that identifies their respective characteristics and limitations. In doing so, it becomes clear that although many of the benefits and savings resulting from MRPII are suitable for inclusion within traditional accountancy frameworks, it is their intangible and non-financial nature, together with a range of indirect project costs that confuse the justification process. These factors, together with a range of human and organisational implications, that further complicate the decision making process are also identified. Hence, it appears through a critical review of the literature that many companies are unable to assess the implications of their MRPII investments, thus amounting to a myopic appraisal process that focuses on the analysis of those benefits and costs that are financially quantifiable. In acknowledging the limitations of traditional appraisal techniques, a conceptual model for IT/IS investment evaluation is proposed, which is underpinned by research hypotheses. To test the validity of the proposed hypotheses, a robust novel research methodology is then developed. In doing so, an interpretivist stance is adopted, which favours the use of qualitative research methods during a multiple case enquiry. Whilst conducting the empirical research, it soon emerged that the hypotheses represented significant factors for consideration within the presented model. As a result, such constructs now establish themselves as integral parts within a structured evaluation process. However, during the empirical research, complementary evaluation criteria also emerged, which resulted in modifications being made to the previously presented conceptual model. In doing so, culminating in the development of descriptive MRPII evaluation criteria and a model, which provides investment decision makers with novel frames of reference during the evaluation of MRPII investment proposals.Department of Manufacturing and Engineering Systems (M&ES), Brunel Universit

Process analytical technology as key-enabler for digital twins in continuous biomanufacturing

Over the last few years rapid progress has been made in adopting well-known process modeling techniques from chemicals to biologics manufacturing. The main challenge has been analytical methods as engineers need quantitative data for their workflow. Industrialization 4.0, Internet of Things, artificial intelligence and machine learning activities up to big data analysis have taken their share in solving fundamental problems like component- or at least group-specific evaluation of spectroscopic data. Besides, concerning inline analytics methods included in process analytical technology concepts the key technology has been the generation of decisive validated digital twins based on process models. This review aims to summarize the methodology to achieve a holistic understanding of process models, control and optimization by means of digital twins using the example of recent work published in this field