Minimum Manufacturing Cost Research Articles

Multiobjective Optimization Design for a Six-Phase Copper Rotor Induction Motor Mounted With a Scroll Compressor

This paper describes a multiobjective optimization design technique for a six-phase copper rotor induction motor mounted with a scroll compressor to achieve minimum manufacturing cost and starting current, and maximum efficiency and power factor. The proposed algorithm uses the modified particle swarm optimization and the Taguchi method with finite-element analysis. The experimental results confirm the validity of the proposed method.

Intellectual Control System of Processing on CNC Machines

Scientific and technical progress makes great demands for quality of engineering production. The priority is to ensure metalworking equipment with required dimensional accuracy during the entire period of operation at minimum manufacturing costs. In article considered the problem of increasing of accuracy of processing products on CNC. The authors offers a solution to the problem by providing compensating adjustment in the trajectory of the cutting tool and machining mode. The necessity of creation of mathematical models of processes behavior in an automated technological system operations (OATS). Based on the research, authors have proposed a generalized diagram of diagnosis and input operative correction and approximate mathematical models of individual processes of diagnosis.

Lean design for Six Sigma

Purpose– The purpose of this paper is to discuss new product development (NPD) based on a traditional stage-gate process and to examine how NPD tools, such as Lean design for Six Sigma, can accelerate the achievement of the main goals of NPD: reliable product quality, cost-effective implementation, and desired time-to-market. These new tools must be incorporated into a new approach to NPD based on the Advanced Product and Quality Planning methodology.Design/methodology/approach– This research paper is based on the theoretical background presented in peer-reviewed scientific research papers during the period 1990-2012. In the second section of this study, the author provides examples of the proposed tools and of advanced techniques to show evidence that validates the hypothesis.Findings– This study presented the theoretical background on the NPD process and related functions in today’s organizations as it relates to competition. NPD was identified as one of the top priorities of every firm, which is why the NPD process must be optimized and oriented toward customers to ensure the quality and reliability of products while minimizing manufacturing costs. The effect on timing and cost is greatly appreciated by top management, and it is well known throughout the firm when a strong, reliable product is launched that it is flawless.Research limitations/implications– To fully deploy all NPD tools requires basic steps such as the following: marketing and planning, design, process, product process validation and the integration of operations from a concurrent engineering standpoint.Practical implications– This research paper provides step by step guidance in order to apply Lean Sigma tool in NPD process in order to achieve Six Sigma quality level in manufacturing.Social implications– Promoting the practice of Lean design for Six Sigma and its tool enables firms to increase their competitiveness since they will make more reliable products delivered to its consumers.Originality/value– The approach of this research paper combines proven statistical tools to be applied in an original sequence in order to design robust product to match manufacturing capabilities.

Optimal Low Carbon Cement Plant via Co-Processing Measure

Cement industry is one of the highest contributor in carbon dioxide (CO2) emissions. With that, this paper proposes the development of a systematic optimization model where minimized production cost is anticipated within the CO2 reduction target and fuels mixture. The optimization models consider co-processing measures which replaces parts of carbon rich fuels with lower carbon fuels in order to achieve lower carbon emissions. The proposed models are executed using General Algebraic Modeling System (GAMS). With highest carbon reduction of 3.2%, the minimum manufacturing cost went from €59.748/t clinker for a 0% carbon reduction target to €65.737/t clinker.

Design of a Gorlov Turbine for Marine Current Energy Extraction

As fossil fuels near depletion and their detrimental side effects become prominent on ecosystems, the world searches renewable sources of energy. Marine current energy is an emerging and promising renewable energy resource. Marine current energy can be alternative energy source for electricity production. Many marine current converters are designed to tap marine current energy; however, Gorlov turbine proves to have minimum manufacturing and maintenance cost, hence giving desired power output. A 0.3m diameter and 0.6m long 3 bladed Gorlov turbine was designed, fabricated and test to analyse its performance. The turbine produces average power 15 W and proves to be quite efficient for marine current energy extraction.

Investigation of Cutting Parameter and Machine Tool Vibration Effects Using Regression Analysis to Enhance Part Dimensional Accuracy

Dimensional accuracy plays important criteria in producing high quality machined parts. This is a big challenge to manufacturers of precision components to produce good quality parts with minimum manufacturing error. The focus of this paper is to study the influence of the machine tool rigidity and cutting parameters on dimensional accuracy in turning operation. A method was prepared for identifying the factors effecting dimensional accuracy in a turning process. Experimental setup involved computerized numerical control (CNC) lathe machine, with VBMT 160404 carbide insert and mild steel, as cutting tool and workpiece respectively. The statistical analysis was used for analyzing and determining the accuracy of experimental data through Minitab statistical software. The regressions model was developed. The developed regression model could be used to predict the dimensional precision of the parts based on machine tool vibration and machining parameters during turning process. This is the aspect to be seriously considered and be applied in attaining sustainable machine tool development during design and development stage and its usage. This finding provides useful guidelines for manufacturers to produce high quality machined parts at minimum manufacturing cost. It was found that the cutting speed, feed rate, final part length, vibration x and vibration z have significant effects on dimensional accuracy of the machined parts.

Statistical tolerance design to minimize dual-responses of APFA height deviations with tolerance cost-quality loss model

Purpose– The purpose of this paper is to apply the statistical tolerancing technique to analyze the dual responses of APFA arm height deviation with respect to next stage of disk assembly process and simultaneously optimize and allocate the required tolerance of the responses onto its components at minimum cost of manufacturing and the quality loss.Design/methodology/approach– The relationships between the dual responses of APFA heights and the geometric dimensions and tolerances of APFA components, and orientation of the assembled part with respect to disk assembly were first defined. The effects of the APFA orientation, and the component tolerances on the distributions and variations of the responses were derived and investigated in terms of resultant product/process performance, quality loss, and the cost of assembly. The tolerance cost-based objective function is then formulated as the combined manufacturing/assembly cost and the quality loss. Direct search method was used to find the best feasible tolerance solutions satisfying the required product performance at minimum cost.Findings– The constructed relationship or transfer functions of the dual responses were probabilistic depending on the orientation of part with respect to the next assembly process. The Monte Carlo simulation is empirically suitable for the computation of the conditional distributions of the responses against the first-order linear approximation of component variances. The proposed solution of tolerance control plan increases the product performances,Cpm, from 0.6 to be at least 1. The proposed tolerance allocation plans will reduce the amount of rework currently as high as 5 percent to at most 0.01 percent with minimally increased assembly cost.Practical implications– This proposed methodology to design and allocate component tolerances is suitable and applicable to the APFA assembly process. The derived assembly functions of probabilistic type relating the responses to the process and component characteristics can represent the actual dynamic of assembled part better than a traditional single deterministic function developed under static concept. This presented methodology can be applied to other assembly cases where quality characteristic depends on the part dynamic.Originality/value– This research simultaneously optimized the dual APFA height deviation responses with minimum cost of tolerance and quality loss using two different conditional distributions and transfer functions of the resultant deviations generated from dynamic of APFA with respect to disk.

REDESIGN AND MANUFACTURING BY USING DMADV METHOD

The cost of poor Quality would help in analyzing the operating costs for effective and profitable business management. . In the era of cut throat competition, especially in automobile sector, success of an organisation resides in its ability to respond quickly to the needs of its customers. These customer needs must be attended with minimum manufacturing costs, minimum lead time to launch the product in market and delivering better performance than the existing competitors in the market.success achieved by market leaders is credited to their improvement initiatives. The customer needs must be attended with minimum manufacturing costs, and delivering better performance than the existing competitors in the market. Therefore, Indian companies in order to compete with global companies, it is very much essential to be at par, in all spheres of business aspects. Cost and Quality are two very important aspects to be globally competitive, to capture market share, to retain customers to be in business and to achieve business excellence. In the present times Six Sigma Methodology and QC Story are very famous and powerful tools and are widely used in the global industries. The increase in demand of the growing customer looking for a better quality of product has compelled corporations to adopt Six Sigma in order to improve the quality for enhanced competitive advantage. Therefore, it is very much essential to understand relation between six sigma and cost of quality and its application in automobile industry.

Implementation of Six Sigma to Reduce Cost of Quality: A Case Study of Automobile Sector

In the era of cut-throat competition, especially in automobile sector, success of an organization resides in its ability to respond quickly to the needs of its customers. These customer needs must be attended with minimum manufacturing costs, minimum lead time to launch the product in market, and delivering better performance than the existing competitors in the market. Six Sigma is a powerful methodology which ultimately helps in cost reduction. Because of defect prevention and improved product and processes, it leads to increase in profitability and market share. This is accomplished through the use of two Six Sigma sub-methodologies: DMAIC and DMADV (Andersson et al., TQM Mag 18:282–296, 2006). By adopting Design For Six Sigma methodology in the design stage itself leads to launch of a product with maximum quality performance, with tighter tolerances, and with reduced or no defects. This paper considers cost of poor quality as the loss imparted to society from the time the product is shipped, and deals with the applications and benefits of Six Sigma methodology and its positive impact on cost of poor quality. A case study is presented, which enabled application of six sigma methodology in wider range of manufacturing activities. This paper is of value to the researcher in the field of quality management, as well as professionals in the manufacturing industry, wherever the quality improvement is an issue. Quality costs or Cost of Quality is a means to quantify the total cost of quality-related efforts and deficiencies (Banuelas and Antony, TQM Mag 14:92, 2002). The “cost of quality” is not the price of creating a quality product or service. It is the cost of NOT creating a quality product or service. Quality Costs represent the difference between the actual cost of a product or service and what the reduced cost would be if there was no possibility of substandard service, failure of products, or defects in their manufacture.

Sustainable Manufacturing based Decision Support Model for Product Design and Development Process

Sustainable manufacturing is creation of manufactured products through economically-sound processes that minimize negative environmental impacts while conserving energy and natural resources. Sustainable manufacturing also enhances employee, community, and product safety. In order to adapt sustainable Manufacturing concepts, it is essential to plan and decide from a product design and development stage as it has been revealed that 80% of sustainability impacts from the product are decided in the product design and development stage. In modern day Products Design and manufacturing it is always advantages to have complete knowledge of the Life Cycle of the Product. If Life cycle information is available for the designers, it will be easy for them to take many decisions related to specially the environmental performance or eco efficiency which is one of the emerging marketing tools. Further, with the full knowledge of the product life cycle, new/existing products can be designed/redesigned based on eco-design principals or environmentally friendly manner, thereby to improve the material and energy efficiency during the manufacturing and user phases and finally will have better environmental performances. The product life cycle and Eco design are two key techniques used in Sustainable Manufacturing specially these will enable to convert any existing product or process to be competitive in the market by better environmental performances and quality while minimizing manufacturing cost beside with better environmental performances. These issues prevail mainly since there is no such systematic approach towards Product Design and Development among the many manufacturers. Since Sustainable Manufacturing Concept applicable for all major phases of the product Life cycle, it is essential to co-relate life cycle assessment outcomes with product design and development process. However, there are numerous decisions needed to take into account at different stages of product design and development process. Therefore, in this research, a decision support model is developed based on LCA and Eco Design concepts. The developed model has been validated with few existing product decision and development processes. The results shows that significant number of issues and potential improvements to the existing design and development processes can be taken from the proposed model and that will leads to many sustainability options to the whole product life cycle than what is persist presently.

Make or Buy Analysis Model Based on Tolerance Design to Minimize Manufacturing Cost and Quality Loss

Make or Buy Analysis Model Based on Tolerance Design to Minimize Manufacturing Cost and Quality Loss

Make or Buy Analysis Model Based on Tolerance Design to Minimize Manufacturing Cost and Quality Loss

In a manufacturing company, manufacturing costs, or component prices, and tolerance will affect the price and the quality of a product. Companies must produce high-quality products with low manufacturing costs in order to keep their products competitive in the market; however, it is difficult to produce a high-quality product with a low manufacturing cost. Companies have difficulties in determining the components to be produced using their own manufacturing facilities (make) or outsourced to their suppliers (buy). Hence, a make or buy analysis is needed to minimize the manufacturing costs and quality loss and to determine the optimum alternative regarding make or buy decisions. This paper discusses an optimization model of a make or buy analysis for a manufacturing company in order to minimize the manufacturing costs and the quality loss in terms of manufacturer and customer quality loss. A numerical example is provided to show the application of the model using a simple assembly product consisting of three components. There are two machines that can be used to produce the components and three alternatives of suppliers to fulfill the order. Each machine and supplier have different characteristics in terms of manufacturing costs and its tolerance.

Supercritical solvent selection (CO2versus ethane) and optimization of operating conditions of the extraction of lycopene from tomato residues: Innovative analysis of extraction curves by a response surface methodology and cost of manufacturing hybrid approach

Lycopene is an important carotenoid present in the large volumes of tomato residues generated annually. Its SFE was studied here with two main objectives: optimization of operating conditions and selection of supercritical solvent (CO2versus ethane). Accordingly, a hybrid approach using the response surface methodology and cost of manufacturing (COM) concept was implemented to establish the best conditions independently of the type of extraction curves available. This approach provides accurate results even in the absence of well-defined periods of extraction (i.e., constant extraction rate branch and the maximum plateau).The minimum COM was 1.8 k€ kglycopene−1 for CO2 at 500 bar/90 °C/25 kgCO2 kgsample−1. At 300bar/60°C the supercritical ethane achieved better results due to the higher extraction rates observed, which originated shorter extraction cycles and thus greater annual productivity and lower COM. More experiments are necessary for an accurate solvent selection, since at 300bar/60°C the CO2 is far from its best performance.

Simultaneous parameter and tolerance optimization of structures via probability-interval mixed reliability model

Both structural sizes and dimensional tolerances strongly influence the manufacturing cost and the functional performance of a practical product. This paper presents an optimization method to simultaneously find the optimal combination of structural sizes and dimensional tolerances. Based on a probability-interval mixed reliability model, the imprecision of design parameters is modeled as interval uncertainties fluctuating within allowable tolerance bounds. The optimization model is defined as to minimize the total manufacturing cost under mixed reliability index constraints, which are further transformed into their equivalent formulations by using the performance measure approach. The optimization problem is then solved with the sequential approximate programming. Meanwhile, a numerically stable algorithm based on the trust region method is proposed to efficiently update the target performance points (TPPs) and the worst case points (WCPs), which shows better performance than traditional approaches for highly nonlinear problems. Numerical results reveal that reasonable dimensions and tolerances can be suggested for the minimum manufacturing cost and a desirable structural safety.

New Operational and Decision Support System for Cutting Process Optimization

Manufacturing cost minimization and productivity maximization are essential for the machining industries sector to survive in the market. The production shop floor is a source of achieving strategic data, providing information to assist cutting processes optimization and better help to use equipment and resources efficiently. In this sense, the objective of this work is to present the development of a New Cutting Process Operational and Decision Support System which is following the most modern computational architecture (this system is being known in Portuguese as SIAPU. The system development is being based on new optimization cutting process approaches. The expectation is that the system offers features as practicability, usability, mobility, beyond contain a help system intuitive on-line. Finally, this work has concluded that the use of the system in industry shop floor can contribute as a remarkable tool to minimize costs or maximize productivity, given to the industries, an opportunity to look for larger profits.

Influence of Built Orientation on Mechanical Properties in Fused Deposition Modeling

Fused deposition modeling (FDM) is one of the thirty techniques of rapid prototyping methods that produce prototypes from polymer materials (natural or with different grades). Acrylonitrile butadiene styrene (ABS) is one of the good material among all polymer materials. It is used in the layer by layer manufacturing of the prototype which is in the semi-molten plastic filament form and built up on the platform from bottom to top. In FDM, one of the critical factor is to select the built up orientation of the model since it affects the different areas of the model like main material, support material, built up time, total cost per part and most important the mechanical properties of the part. In view of this, objective of the present study was to investigate the effect of the built-up orientation on the mechanical properties and total cost of the FDM parts. Experiments were carried out on STRATASYS FDM type rapid prototyping machine coupled with CATALYST software and ABS as main material. Tensile and Impact specimens were prepared as per the ASTM standard with different built-up orientation and in three geometrical axes. It can be concluded from the experimental analysis that built orientation has significant affect on the tensile, impact and total cost of the FDM parts. These conclusions will help the design engineers to decide on proper build orientation, so that FDM parts can be fabricated with good mechanical properties at minimum manufacturing cost.

A comparative study of preference dominance-based approaches for selection of industrial robots

A B S T R A C T A R T I C L E I N F O In the modern era of highly mechanized technologies, manufacturing organizations are now extensively using different kinds of industrial robots for performing complicated and perilous tasks with superior levels of accuracy. The major role of robotic technology within manufacturing organizations is to amalgamate design, manufacturing and management planning activities into a flexible system for improving production lines with minimum manufacturing cost involvement. However, the pre-implementation, implementation, and post-implementation phases of robotic technologies are the foremost issues associated with the selection and rationalization of robotic investments, which is based on a thorough review and exploration of various alternative robots and their mutually conflicting performance measures. Evaluating alternative robots in the presence of multiple conflicting attributes often makes the selection task very complex. This paper focuses on the application feasibilities of two preference dominance-based multi-attribute decision-making (MADM) approaches, namely evaluation of mixed data (EVAMIX) and extended preference ranking organization method for enrichment evaluation II (EXPROM2) whilst selecting the best alternative robots within given manufacturing environments. Using these two methods, a list of all the feasible alternatives from the best to the worst suitable robot is obtained by taking into account different robot selection attributes. The ranking performances of these methods are also compared with those of the past researchers, using four performance tests.

Tool life based cutting parameter selection in high speed milling of ceramic–PTFE composites

Based on tool life in high speed milling of ceramic–polytetrafluoroethylene (PTFE) composites, an approach to select optimal cutting parameters is presented. With tool wear data recorded in experimental process, a BP neural network was constructed as a bridge between experimental data and response surface methodology. Nonlinear relationship of tool wear with cutting speed, feedrate, axial depth of cut, radial depth of cut and cutting length was mapped with neural network. Using samples generated by BP neural network, tool life model was built with quadratic response surface equation, which gives stable and feasible outputs. With tool life model, an optimisation model for minimal manufacturing cost was built. Further optimisation was conducted with genetic algorithm to get optimal cutting parameters. The method can be used to decrease manufacturing cost or improve productivity.

Supercritical Fluid Extraction Of Lemon Verbena (Aloysia triphylla): Process Kinetics and Scale-Up, Extract Chemical Composition and Antioxidant Activity, and Economic Evaluation

The extract of lemon verbena ( Aloysia triphylla ) was obtained by supercritical fluid extraction (SFE) using laboratory and pilot scale equipments. The scale-up criterion selected (maintaining solvent to feed ratio constant) was successfully used for a 14-fold scale-up. The extract obtained in pilot scale was separated in three fractions, which were characterized as for their phytochemical profile, total flavonoids content, and antioxidant activity. The extracts obtained by SFE were compared to classical Soxhlet extraction method. Maximum yield obtained for SFE was 1.8%, and for Soxhlet, 7.1%. The chemical composition revealed different phytochemical profiles for SFE and Soxhlet extracts; the last ones presented more flavonoids, while SFE extracts were more concentrated in volatile compounds. The major compounds identified in the volatile fraction of the extracts were spathulenol, phytol and octadecatrienal. Some extracts presented pro-oxidant activity and others presented antioxidant activity. The SFE process was shown to be economically feasible for obtaining lemon verbena extracts; the minimum manufacturing cost (COM) obtained was US$ 1070.00/kg, with a payback time of 2 years.

Minimum Costs for Producing Hepatitis C Direct-Acting Antivirals for Use in Large-Scale Treatment Access Programs in Developing Countries

Several combinations of 2 or 3 direct-acting antivirals (DAAs) can cure hepatitis C virus (HCV) in the majority of treatment-naive patients. DAAs for HCV infection have similar mechanisms of action and chemical structures to antiretrovirals for human immunodeficiency virus (HIV) infection. Generic antiretrovirals are currently manufactured at very low prices, to treat 10 million people with HIV/AIDS in developing countries. Four HCV DAAs, currently either in phase 3 development or recent approval (daclatasvir, sofosbuvir, simeprevir, faldaprevir), and ribavirin were classified by chemical structure, molecular weight, total daily dose, and complexity of synthesis. The likely range of manufacturing costs per gram of DAA were then projected as formulated product cost, based upon treating a minimum of 1 million patients annually (to arrive at volume demand) combined with an analysis of the complexity of synthesis and a 40% margin for formulation. Projections were then compared with actual costs of antiretrovirals with similar structures. Minimum manufacturing costs of antiretrovirals were US$0.2-$2.1 per gram. The complexity of chemical synthesis for HCV DAAs was ranked from lowest to highest: ribavirin, daclatasvir, sofosbuvir, faldaprevir, and simeprevir. Predicted manufacturing costs (US dollars) for 12-week courses of HCV DAAs were $21-$63 for ribavirin, $10-$30 for daclatasvir, $68-$136 for sofosbuvir, $100-$210 for faldaprevir, and $130-$270 for simeprevir. Within the next 15 years, large-scale manufacture of 2 or 3 drug combinations of HCV DAAs is feasible, with minimum target prices of $100-$250 per 12-week treatment course. These low prices could make widespread access to HCV treatment in low- and middle-income countries a realistic goal.