Process-controlled machining of gray cast iron

Fischer, Glenn A.; Wei, Yui; Dontamsetti, Satya

doi:10.1016/0378-3804(89)90017-x

Cited by 4 publications

(3 citation statements)

References 5 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The tool life model, serving as a guide for optimization of cutting performance, showed that the cutting speed "V c " is the most influential parameter on tool life and, to a lesser extent, the depth of cut "DOC" and feed rate "FR". Fischer et al [2] conducted turning experiments on grey cast iron using WC insert and established a multi-objective goal optimization model suggesting that the "V c " and "FR" can be calculated and altered aiming to a specific surface roughness. Cutting tool performance was evaluated by Souza et al [3], who conducted turning runs on grey cast iron using a Si 3 N 4 -based ceramic tool at various "V c " and "FR", whereas the "DOC" was maintained constant.…”

Section: Introductionmentioning

confidence: 99%

Investigation and Statistical Analysis for Optimizing Surface Roughness, Cutting Forces, Temperature, and Productivity in Turning Grey Cast Iron

Rayes

Abbas

Al-Abduljabbar

et al. 2023

Metals

View full text Add to dashboard Cite

This paper investigated the influence of cutting parameters, including feed rate, cutting speed, tool nose radius, and wet or dry cutting conditions, on the resultant force, cutting edge/workpiece temperature, and surface roughness when turning grey cast iron. Results showed that increasing the feed rate increased the resultant force, cutting temperature, and surface roughness. At the same time, increasing the cutting speed and nose radius increased the cutting temperature, which in turn reduced the resultant force. For practical applications, basic mathematical calculations based on the sole effect of each parameter on the output of the experiments were used to estimate the extent of percentage increase in cutting temperature due to increasing feed rate, cutting speed, and nose radius. Similarly, the same approach was used to estimate the effect of increasing feed rate, cutting speed, and nose radius on average surface roughness. Results showed that increasing the feed rate increases the cutting temperature by 5 to 11% depending on the nose radius and cutting speed. On the other hand, increasing the cutting speed was found to have limited effect on cutting temperature with small nose radius whereas this effect increases with increasing the nose radius reaching about 11%. Increasing the nose radius also increases the cutting temperature, depending mainly on cutting speed, reaching a maximum of 21% at higher cutting speeds. Results also showed that increasing the feed rate increased the average surface roughness considerably to about 120% at high cutting speeds and a large nose radius. On the other hand, increasing the cutting speed and nose radius reduced the surface roughness (i.e., improved surface quality) by a maximum of 29 and 23%, respectively. In order to study the combined effects of the cutting parameters on the three responses, namely, the resultant cutting force, cutting temperature, and surface roughness, full factorial design and ANOVA were used, where it was found to be in good agreement with mathematical calculations. Additionally, the desirability function optimization tool was used to minimize the measured responses whilst maximizing the material removal rate.

show abstract

Section: Introductionmentioning

confidence: 99%

Investigation and Statistical Analysis for Optimizing Surface Roughness, Cutting Forces, Temperature, and Productivity in Turning Grey Cast Iron

Rayes

Abbas

Al-Abduljabbar

et al. 2023

Metals

View full text Add to dashboard Cite

show abstract

“…The later part of the chapter was dedicated to the machining economics problem. Programming model [9] was used to calculate optimum cutting speed, and feed for a given depth of cut and cutting tool, thus satisfying the surface finish, and machine power constraints.…”

Section: Resultsmentioning

confidence: 99%

“…Ever since, many mathematical models have been developed to determine the optimum cutting conditions for either single pass or multi-pass turning. Extensive literature review revealed that Geometric Programming [18], [29] and [30]; Lagrange multiplier [2]; a combination of linear and geometric programming [8]; and Goal programming [9] and [23] were some of the optimization techniques used by researchers in this area. An analytical approach to select machining parameters for turning with constraints was developed by Gopalakrishnan and Al-Khayyal [10] based on geometric programming; F.P.…”

Section: Machining Economicsmentioning

confidence: 99%

Design and development of a target-costing model for machining

Kokatnur¹

View full text Add to dashboard Cite

In today's intensely competitive and highly volatile business environment, consistent development of low cost and high quality products meeting the functionality requirements is a key to a company's survival. Companies continuously strive to reduce the costs while still producing quality products to stay ahead in the competition. Many companies have turned to target costing to achieve this objective. Target costing is a structured approach to determine the cost at which a proposed product, meeting the quality and functionality requirements, must be produced in order to generate the desired profits. It subtracts the desired profit margin from the company's selling price to establish the manufacturing cost of the product. Extensive literature review revealed that companies in automotive, electronic and process industries have reaped the benefits of target costing. However target costing approach has not been applied in the machining industry, but other techniques based on Geometric Programming, Goal Programming, and Lagrange Multiplier have been proposed for application in this industry. These models follow a forward approach, by first selecting a set of machining parameters, and then determining the machining cost. Hence in this study we have developed an algorithm to apply the concepts of target costing, which is a backward approach that selects the machining parameters based on the required machining costs, and is therefore more suitable for practical applications in process improvement and cost reduction. A target costing model was developed for turning operation and was successfully validated using practical data.

show abstract

Development of a framework to automate process planning functions and to determine machining parameters

Narang

Fischer

1993

International Journal of Production Research

View full text Add to dashboard Cite

Process-controlled machining of gray cast iron

Cited by 4 publications

References 5 publications

Investigation and Statistical Analysis for Optimizing Surface Roughness, Cutting Forces, Temperature, and Productivity in Turning Grey Cast Iron

Investigation and Statistical Analysis for Optimizing Surface Roughness, Cutting Forces, Temperature, and Productivity in Turning Grey Cast Iron

Design and development of a target-costing model for machining

Development of a framework to automate process planning functions and to determine machining parameters

Contact Info

Product

Resources

About