Optimization Of Engineering Processes Research Articles

Engineering Process Optimization and Quality Stability Control of High-Speed Laser Cladding Coatings Based on AHP-FCE

Due to the rapid advancement in processing efficiency, high-speed laser cladding has demonstrated significant potential in the repair and protection of various substrates. In this study, we established a comprehensive evaluation model for the coating quality of Fe-Cr-Ni-based alloy with high-speed laser cladding using the analytic hierarchy process and fuzzy comprehensive evaluation method (AHP-FCE). The weights obtained through the analytic hierarchy process for forming quality, microstructure, and surface performance are as follows: WB1 = 0.1365, WB2 = 0.2385, and WB3 = 0.625, respectively. During the fuzzy comprehensive evaluation step, an evaluation level was graded while quantifying the level range through membership function judgment. By combining subjective and objective evaluations, qualitative issues were transformed into quantitative assessment methods. Through comprehensive evaluation analysis, it was concluded that the scanning speed of high-speed laser cladding had a greater impact on coating thickness compared to powder feeding speed while significantly enhancing microstructure densification. The overlap rate exerted the most influence on dilution rate homogenization of near-surface dendrites. Simultaneously, the optimal preparation technology was determined: laser power 660 W, scanning speed 14,400 mm/min, overlap rate/min. This study transforms multi-objective quality evaluation of high-speed laser cladding coatings into a single objective problem by realizing comprehensive quality quantification and providing a new method for quantitative evaluation and visualization of coating quality.

Digital Twin for the Transient Temperature Prediction During Coaxial One-Side Resistance Spot Welding of Al5052/CFRP

Abstract In the present research, a digital twin of coaxial one-side resistance spot welding (COS-RSW) was established for the real-time prediction of transient temperature field. A three-dimensional (3D) model of COS-RSW joint was developed based on the in-house finite element (FE) code JWRIAN-SPOT. The experimental verified FE model was employed to generate the big data of temperature of COS-RSW process. Multiple dimension interpolation was applied to process database and output prediction. The FE model can predict the thermal cycle on COS-RSW joints under different parameter couples. The interpolation effect of individual welding parameters was discussed, and a power weight judgement for welding time was essential to ensure accuracy. With the support of big data, the digital twin can provide visualization prediction of COS-RSW within 10 s, whereas numerical modeling needs at least 1 h. The proposed application of digital twin has potential to improve the efficiency of process optimization in engineering.

Collaboration and Optimization Processes Contribute to Ultra-ERD Offshore Well Success

This article, written by JPT Technology Editor Judy Feder, contains highlights of paper SPE 202251, “Transforming the Mindset To Drill Ultra-ERD Wells With High Tortuosity,” by Barry Goodin, SPE, Duane Selman, and Andy Wroth, Vermilion Oil and Gas, et al., prepared for the 2020 SPE Asia Pacific Oil and Gas Conference and Exhibition, originally scheduled to be held in Perth, Australia, 20–22 October. The paper has not been peer reviewed. The complete paper describes the extensive integrated engineering collaboration and optimization process that allowed an operator to push the drilling and completion envelope to drill a pair of complex, ultra-extended-reach-drilling (ERD) wells in the mature Wandoo field in the Carnarvon Basin offshore Western Australia. The shallow reservoir depth, extreme ERD profile, and high tortuosity requirement for the wells posed significant challenges. These were overcome with extensive planning; integrated engineering designs; application of new technology; good-quality, real-time data interpretation; and strong execution support from both rig site and town. Introduction The Wandoo field, in 56 m of water off-shore Western Australia, was discovered in 1991 and subsequently developed and placed on production in 1993. The shallow unconsolidated sandstone reservoir consists of a heavily biodegraded oil column overlain by a gas cap and supported by a strong aquifer drive. Field infrastructure consists of a 15-well-slot manned production facility, Wandoo B, and a five-slot monopod, Wandoo A, which is tied back to Wandoo B by subsea in-field pipelines. In late 2018, the operator planned and executed a two-well drilling campaign consisting of two complex, ultra-ERD wells, Wandoo B15 and B16. Both wells were planned to be batch drilled for the top hole and intermediate hole sections, with the production hole sections to be drilled and completed sequentially. The primary objective for the B15 well was to recover unswept oil along the western flank of the field and track the well along the main Wandoo fault to the north to assess the structure and reserves from the northern tip of the field. The B16 well objective was to access unswept reserves through the center and down to the south of the field, essentially twinning the B11ST1 well, another ERD well drilled on an earlier campaign, to its eastern flank. To maximize recovery, both wells needed to be placed approximately 1 m below the top of the reservoir, except where overlain by the gas cap, in which case the wells were to be placed approximately 2 m below the gas/oil contact to avoid gas coning. Drilling Challenges and Solutions The first half of the complete paper presents a detailed discussion of the drilling challenges and solutions, illustrated with schematics, maps, charts, and graphs. Both Wells B15 and B16 were classified as ultra-ERD wells because the shallow true vertical depth (TVD) of the reservoir resulted in extreme stepout ratios and required highly complex well paths to access the remaining reserves. The complete paper lists various specific drilling- and systems-related challenges.

ДИАГНОСТИКА ТЕХНОЛОГИЧЕСКОЙ СИСТЕМЫ РЕЗАНИЯ С ПРИМЕНЕНИЕМ ПАРАМЕТРОВ СИЛЫ РЕЗАНИЯ

The purpose of this work: the engineering process optimization of 09H17N7Yu steel turning at the expense of creating the procedure allowing the diagnostics of an engineering cutting system state on the results of cutting force control, inverse problem solution, that is, cutting force control according to the analysis results of system state diagnostics, the optimization of cutting mode parameters to ensure the required values of a cutting force, on the basis of the analysis results of a cutting force the tool materials and tool geometry should be recommended for cutter wear-resistance increase, the prediction of tool life at the expense of designing new tool materials and tool geometry for new conditions of their operation. 
 There are presented recommendations to ensure a correct choice of carbide cutting inserts quality for the specified conditions of their operation. On the investigation results there are obtained conclusions: the most promising for special stainless steel 09H17N7Yu turning were tool materials: TC8+TiCN(mkm) + (TiAl)N(3mkm) + Al2O3(5mkm) + TiC(5mkm); TC8+Al2O3(2mkm) + (Ti)CN(5mkm) + (TiAl)N(3mkm) + TiN(3mkm); TC8 + (TiAl)N(3mkm) + Al2O3(3mkm) + (TiAl)N(3mkm) + Al2O3(3mkm); it is defined that at cutting mode forcing (cutting speed 60m/min, depth 2.5mm) or at turning titanium alloy TT-22 more complex in machining the mentioned tool materials met the demands made, that is, real insert life varied from the designed one not considerably (in the first case – 7% maximum, in the second one – 14%), that is the most acceptable. Work novelty: there is offered and substantiated a procedure for cutting force constituents use on the basis of simulation for the choice or design of tool material for turning in different conditions of tool operation.

ДИАГНОСТИКА ТЕХНОЛОГИЧЕСКОЙ СИСТЕМЫ РЕЗАНИЯ С ПРИМЕНЕНИЕМ ПАРАМЕТРОВ СИЛЫ РЕЗАНИЯ

The purpose of this work: the engineering process optimization of 09H17N7Yu steel turning at the expense of creating the procedure allowing the diagnostics of an engineering cutting system state on the results of cutting force control, inverse problem solution, that is, cutting force control according to the analysis results of system state diagnostics, the optimization of cutting mode parameters to ensure the required values of a cutting force, on the basis of the analysis results of a cutting force the tool materials and tool geometry should be recommended for cutter wear-resistance increase, the prediction of tool life at the expense of designing new tool materials and tool geometry for new conditions of their operation. 
 There are presented recommendations to ensure a correct choice of carbide cutting inserts quality for the specified conditions of their operation. On the investigation results there are obtained conclusions: the most promising for special stainless steel 09H17N7Yu turning were tool materials: TC8+TiCN(mkm) + (TiAl)N(3mkm) + Al2O3(5mkm) + TiC(5mkm); TC8+Al2O3(2mkm) + (Ti)CN(5mkm) + (TiAl)N(3mkm) + TiN(3mkm); TC8 + (TiAl)N(3mkm) + Al2O3(3mkm) + (TiAl)N(3mkm) + Al2O3(3mkm); it is defined that at cutting mode forcing (cutting speed 60m/min, depth 2.5mm) or at turning titanium alloy TT-22 more complex in machining the mentioned tool materials met the demands made, that is, real insert life varied from the designed one not considerably (in the first case – 7% maximum, in the second one – 14%), that is the most acceptable. Work novelty: there is offered and substantiated a procedure for cutting force constituents use on the basis of simulation for the choice or design of tool material for turning in different conditions of tool operation.

Numerical study of sound generation by three-dimensional flexible flapping wings during hovering flight

In this paper, the sound generated by three-dimensional flexible flapping wings during hovering flight is numerically studied by using an immersed boundary method. The wing shape, prescribed motion of the wing leading edge, Reynolds number, wing-to-fluid mass ratio and wing flexibility are systematically examined. The numerical results show that these governing parameters have a significant influence on the aerodynamic performances and consequently the acoustic outputs. The comparisons among four wing shapes indicate that the wing shape does not influence the sound directivity. The wing with larger area close to the wing-tip generates more lift associated with a larger acoustic output. The systematic examinations of four pitching amplitudes suggest that the optimal one is π∕2, which provides the highest efficiency with the lowest acoustic output. The effects of the flexibility are examined at two wing-to-fluid mass ratios (i.e., m∗=1.0 and 5.0) with the dimensionless flapping frequency ω∗ ranging from 0 to 0.5. The results show that an appropriate flexibility enhances the aerodynamic performance and reduces the acoustic outputs. The optimal choice is to use a flexible wing whose inertia is comparable to its aerodynamics, i.e., m∗=1.0 and ω∗=0.3, by which the highest efficiency is achieved with a relatively low acoustic outputs (30.5% lower than that of a rigid wing) and high lift generation. By collecting all the numerical data together, a linear relationship of the sound power and the root-mean-square of the power coefficient is observed. By using the fitted equation, the acoustic outputs of a flapping wing can be directly obtained from its aerodynamics, which can be used to simplify the engineering design and optimization process considering acoustic outputs.

A hybrid multi‐objective tour route optimization algorithm based on particle swarm optimization and artificial bee colony optimization

SummaryComputational intelligence techniques have widespread applications in the field of engineering process optimization, which typically comprises of multiple conflicting objectives. An efficient hybrid algorithm for solving multi‐objective optimization, based on particle swarm optimization (PSO) and artificial bee colony optimization (ABCO) has been proposed in this paper. The novelty of this algorithm lies in allocating random initial solutions to the scout bees in the ABCO phase which are subsequently optimized in the PSO phase with respect to the velocity vector. The last phase involves loyalty decision‐making for the uncommitted bees based on the waggle dance phase of ABCO. This procedure continues for multiple generations yielding optimum results. The algorithm is applied to a real life problem of intercity route optimization comprising of conflicting objectives like minimization of travel cost, maximization of the number of tourist spots visited and minimization of the deviation from desired tour duration. Solutions have been obtained using both pareto optimality and the classical weighted sum technique. The proposed algorithm, when compared analytically and graphically with the existing ABCO algorithm, has displayed consistently better performance for fitness values as well as for standard benchmark functions and performance metrics for convergence and coverage.

Gradual tool-based optimization of engineering processes aiming at a knowledge-based configuration of robot-based automation solutions

Due to the growing individualization and ever shorter product life cycles, the engineering of automation solutions is facing increasing challenges. The rethinking of common engineering processes and the inclusion of knowledge-based approaches are considered inevitable. However, existing optimization measures often do not meet the actual problems as many approaches in academics are still too immature for practical use. Therefore, a rather simple procedure for the optimization of knowledge-intensive engineering processes is presented here, mainly relying on the incremental, tool-based creation of a common knowledge base. The procedure is validated using the example of a German automotive supplier. Building on this, the further development towards a knowledge-based configuration platform for robot-based automation solutions is illustrated in the outlook.

Mathematical modeling and numerical investigation of carbon capture by adsorption: Literature review and case study

The carbon capture by adsorption (CCA) is regarded as an available engineering technology because of its low energy-consumption, easy to control, and possible integration with renewable energy. The recent advances in CCA research comprises mainly about the performance improvement of adsorbents, design and optimization of engineering process. However, considering the time-consuming and intensive funding required for experimental investigation, the numerical simulation has been widely applied in CCA. In numerical simulation field of CCA, the adsorption process is commonly simplified into mathematical models group comprised of adsorption kinetics model, the adsorption equilibrium model, pressure drop model and heat transfer model. However, few studies’ focus is to provide a detailed review of the research methodology of mathematical modeling in CCA simulation.This paper presents a pathway map on CCA mathematical modeling through literature review and case study. An overview of model screening and modeling method of CCA is provided in the review part. This part also provides a short guided tour on how to combine the fundamental models about heat and mass transfer together to form a model group for various application scenarios in CCA. Then the pathway map on CCA modeling, which is summarized based on the review, is applied to a case study. In this part, the adsorption of CO2/N2 mixtures on activated carbon under the conditions of high temperature and low pressure is numerically investigated based on the established models. The performance indicators comprise gas temperature, mole fraction, and adsorbate amount of the fixed bed, are applied in the evaluation performance of CCA. Based on the proposed methodology, the CCA modeling demonstrates a more fluent design process relative to the real physical scenario, with a possible access to further optimization. Particularly, the simulation results showed that the optimized dimensionless velocity for the highest utilization efficiency of the fixed bed can be obtained and thus is proposed as 1.2–1.4 for the most suitable feed velocity to fit different size of fixed bed and different types of adsorbents for the engineering design.

Mechanical property research of different materials for supporting rings.

Supporting rings are becoming more widely applied as an assistant structural support. However, during the engineering design and optimization process, many tests are necessary to understand the mechanical properties of different materials and the different section shape for supporting rings. The key problem is to measure the radial force caused by elongation under the axes' pressure. This cannot be measured directly through the use of sensors. The previous, simple method was to position a transfer bar into the hole on the supported wall, or use a strain gauge, which changes the contact boundary. A new method called the "semi-ring method" is proposed. The problem can be solved well and the feasibility of this method is shown from an example of its application. An innovative method is applied in test of mechanical performance for PTFE and butyl rubber material adopted in four kinds of section shape structure supporting rings. The results and analysis can provide some beneficial references for structure design.

A stochastic optimization framework for road traffic controls based on evolutionary algorithms and traffic simulation

Traffic flow is considered as a stochastic process in road traffic modeling. Computer simulation is a widely used tool to represent traffic system in engineering applications. The increased traffic congestion in urban areas and their impacts require more efficient controls and management. While the effectiveness of control schemes highly depends on accurate traffic model and appropriate control settings, optimization techniques play a central role for determining the control parameters in traffic planning and management applications. However, there is still a lack of research effort on the scientific computing framework for optimizing traffic control and operations and facilitating real planning and management applications. To this end, the present study proposes a model-based optimization framework to integrate essential components for solving road traffic control problems in general. In particular, the framework is based on traffic simulation models, while the solution needs extensive computation during the engineering optimization process. In this work, an advanced genetic algorithm, extended by an external archive for storing globally elite genes, governs the computing framework, and in application it is further enhanced by a sampling approach for initial population and utilizations of adaptive crossover and mutation probabilities. The final algorithm shows superior performance than the ordinary genetic algorithm because of the reduced number of fitness function evaluations in engineering applications. To evaluate the optimization algorithm and validate the whole software framework, this paper illustrates a detailed application for optimization of traffic light controls. The study optimizes a simple road network of two intersections in Stockholm to demonstrate the model-based optimization processes as well as to evaluate the presented algorithm and software performance.

A generic cloud platform for engineering optimization based on OpenStack

Optimizations have been applied in many different engineering fields. Most of these applications may have similar characteristics: intensive on computing resources, time-consuming on calculation iterations, similar on computing environments and so on. This paper describes a generic cloud platform for engineering optimization by leveraging the compute resources hosted in cloud datacenters. The methodology developed was to decompose the engineering optimization processes into several interconnected sub-tasks, which were further converted and implemented as virtual applications for dynamic cloud deployment using OpenStack. The system can dynamically allocate and recycle the compute resources according to the specific engineering optimization applications. The research presented in the paper contributes on the generic engineering optimization process virtualization and cloud computing based implementation with innovative algorithms development. The system test results showed a way that potentially engineering optimization problems could be embedded into the put forward platform due to the developed large scale and intelligent cloud based optimization services. Further applications for building energy simulation and optimization, stents optimization, water distribution optimization are currently under development.

Enhanced Specificity of TPMT*2 Genotyping Using Unidirectional Wild-Type and Mutant Allele-Specific Scorpion Primers in a Single Tube

Genotyping of thiopurine S-methyltransferase (TPMT) is recommended for predicting the adverse drug response of thiopurines. In the current study, a novel version of allele-specific PCR (AS-PCR), termed competitive real-time fluorescent AS-PCR (CRAS-PCR) was developed to analyze the TPMT*2 genotype in ethnic Chinese. This technique simultaneously uses wild-type and mutant allele-specific scorpion primers in a single reaction. To determine the optimal conditions for both traditional AS-PCR and CRAS-PCR, we used the Taguchi method, an engineering optimization process that balances the concentrations of all components using an orthogonal array rather than a factorial array. Instead of running up to 264 experiments with the conventional factorial method, the Taguchi method achieved the same optimization using only 16 experiments. The optimized CRAS-PCR system completely avoided non-specific amplification occurring in traditional AS-PCR and could be performed at much more relaxed reaction conditions at 1% sensitivity, similar to traditional AS-PCR. TPMT*2 genotyping of 240 clinical samples was consistent with published data. In conclusion, CRAS-PCR is a novel and robust genotyping method, and the Taguchi method is an effective tool for the optimization of molecular analysis techniques.

Taguchi optimization of duplex PCR for simultaneous identification ofStaphylococcus aureusandClostridium perfringensalpha toxins

Staphylococcus aureus and Clostridium perfringens are two major bacteria that infect open wounds and delay the healing process. The rapid and progressive deterioration of soft tissue during S.aureus and C.perfringens coinfections is due to analogous necrotic alpha toxins produced by the two organisms. The aim of this study was to determine the alpha toxins of S.aureus and C.perfringens by duplex PCR. The PCR assay employed two sets of primers: hlaf/r to amplify staphylococcal alpha toxin gene hla (274bp) and cpaf/r to amplify clostridial alpha toxin gene cpa (398bp) along with a competitive internal amplification control (608bp), simultaneously. Optimization of the duplex PCR assay was achieved by a modified Taguchi method, an engineering optimization process, in a nine-tube combinatorial array. The detection level of the duplex PCR was found to be 10pg of purified DNA or 10(3) CFUmL(-1) of S.aureus and 100pg of purified DNA or 10(4) CFUmL(-1) of C.perfringens. Other bacteria routinely found in tissue infections were tested for cross-reactivity and the duplex PCR turned out to be highly specific. This duplex PCR assay provides a rapid, robust and reliable alternative to the existing conventional techniques in establishing the aetiology of S.aureus and C.perfringens in soft tissue infections.

Optimization of Engineering Processes in Factory Planning

Currently, social media software is widely used for many fields but not yet in factory planning and specifically for cooperative planning processes and in the realization phase of production systems. Motivated by the growing potential of factory planning and the need to eliminate shortcomings within communication and cooperation during planning and realization of production systems, this paper describes a procedure and a prototype for supporting communication, collaboration and knowledge management in factory planning projects with social media technology. This procedure was developed in cooperation with the factory planners of Chemnitz University of Technology and the software specialists of the community4you GmbH. The procedure is based on a reference model and building blocks for planning assignments that can be used later on for different planning projects and planning cases. Thus, the existing methodology for factory planning will be extended, in this case by adding a procedure for communication and collaboration. A prototype is developed, following the guidelines of the mentioned procedure, and the building blocks are transferred to software modules.

Robust Engineering of Deep Drilling Process by Surface State Optimization

The off-line quality engineering is an important aspect that regards the manufacturing engineering process optimization. This target may be achieved by implementing the robust engineering principles. Therefore, the present paper reflects the results of the Taguchi Method approach applied for a fractioned factorial designed experiment in case of deep peck drilling with a twist drill, of a composite material. The scope was to optimize the surface state, characterized by his roughness, optically measured.

Using the Taguchi method for rapid quantitative PCR optimization with SYBR Green I

Here, we applied the Taguchi method, an engineering optimization process, to successfully determine the optimal conditions for three SYBR Green I-based quantitative PCR assays. This method balanced the effects of all factors and their associated levels by using an orthogonal array rather than a factorial array. Instead of running 27 experiments with the conventional factorial method, the Taguchi method achieved the same optimal conditions using only nine experiments, saving valuable resources.

Nitrogen removal performance and microbial community structure dynamics response to carbon nitrogen ratio in a compact suspended carrier biofilm reactor

A compact suspended carrier biofilm reactor (SCBR) was developed for simultaneous nitrification and denitrification (SND) in a single reactor and the performance of nutrient removal was investigated. Microbial community structure response to different ratio of carbon to nitrogen (C/N) was determined by denaturing gel gradient electrophoresis (DGGE) profiles of 16S rDNA V3 region and amoA gene amplifications. In addition, the population dynamics of ammonia-oxidizing bacteria (AOB) and nitrite-oxidizing bacteria (NOB) were estimated by fluorescence in situ hybridization (FISH) with 16S rDNA-targeted oligonucleotide probes. Results showed that the compact SCBR was efficient in nutrient removal with COD Cr removal efficiency over 90% and SND efficiency ( E SND) about 83.3%. The diversity of microbial community structure was positively correlated with C/N ratio, while the three communities of amoA gene were relativity homogenous. The population of nitrifiers was in inverse proportions to C/N ratio with the average fraction of AOB and NOB to all bacteria 5.4, 4.8, 3.1% and 4.6, 3.5, 2.7% respectively as C/N ratio changing from 3:1, 5:1 to 10:1. Therefore we could reach a conclusion that the compact SCBR was practical to treat municipal wastewater and the shift of microbial community monitored by molecular technologies could offer guidance to the process optimization in engineering.

Minimizing the entropy production in a chemical process for dehydrogenation of propane

We minimize the total entropy production of a process designed for dehydrogenation of propane . The process consists of 21 units, including a plug-flow reactor, a partial condenser, two tray distillation columns and a handful of heat exchangers and compressors. The units were modeled in a manner that made them relatively insensitive to changes in the molar flow rates , to make the optimization more flexible. The operating conditions, as well as to some degree the design of selected units, which minimized the total entropy production of the process, were found. The most important variables were the amount of recycled propane and propylene , conversion and selectivity in the reactor, as well as the number of tubes in the reactor. The optimal conversion, selectivity and recycle flows were results of a very clear trade-off among the entropy produced in the reactor, the partial condenser and the two distillation columns. Although several simplifying assumptions were made for computational reasons, this shows for the first time that it is also meaningful to use the entropy production as an objective function in chemical engineering process optimization studies.