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Relevant bibliographies by topics / Setup planning

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Journal articles

Academic literature on the topic 'Setup planning'

Author: Grafiati

Published: 4 June 2021

Last updated: 1 February 2022

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Journal articles on the topic "Setup planning"

1

Šormaz, Dušan, Mayur Wakhare, and Nur-Ul Arafat. "RULE-BASED PROCESS PLANNING AND SETUP PLANNING WITH CONSIDERATIONS OF GD&T REQUIREMENTS." International Journal "Advanced Quality" 45, no. 1 (2017): 13. http://dx.doi.org/10.25137/ijaq.n1.v45.y2017.p13-20.

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Computer aided process planning is a critical link between design and manufacturing. The ready process plan in integration of design and manufacturing is always important to save manufacturing time, reduction of work in progress. This paper describes a rule based intelligent process planning system which selects necessary manufacturing processes features in the metal mechanical parts. Novel feature of this system is the use of detailed GD&T specification on both process selection and setup planning modules. Process selection module selects the necessary processes for manufacturing the hole feature that depends on feature dimensions, feature precedence, and specified geometric and dimensional tolerances. Setup planning module determines the sequences of the setups of the prismatic part on the machine tools that includes clustering and sequencing of the features in setups. This module uses rules for the following steps: tool approach direction definition, setup formation based on GD&T requirements, resolution of possible cyclic setups, setup sequencing and operation sequencing in setups. Rules can generate valid setups for both 3-axis and 4-axis milling machines. The procedures are illustrated on several examples.

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Gupta, S. K., and D. A. Bourne. "Sheet Metal Bending: Generating Shared Setups." Journal of Manufacturing Science and Engineering 121, no. 4 (1999): 689–94. http://dx.doi.org/10.1115/1.2833107.

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Contemporary process planners for sheet metal bending solve the process planning problem for individual parts. Quite often, many different parts can be produced on shared setups. However, plans generated by current process planning systems fail to exploit this commonality between setups and try to generate optimal setups for individual parts. In this paper, we present an algorithm for multi-part setup planning for sheet metal bending. This algorithm takes a set of parts and operation sequences for these parts, and tries to find a shared setup plan that can work for every part in the set. Setup changes constitute a major portion of the production time in batch production environments. Therefore, multi-part setup planning techniques can be used to significantly cut down the total number of setups and increase the overall through-put.

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3

Wakhare, Mayur, and Dušan Šormaz. "Sequencing of Setups in Automated Setup and Fixture Planning." Procedia Manufacturing 5 (2016): 41–57. http://dx.doi.org/10.1016/j.promfg.2016.08.007.

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4

Baan, F., O. de Waard, R. Bruggink, T. Xi, E. M. Ongkosuwito, and T. J. J. Maal. "Virtual setup in orthodontics: planning and evaluation." Clinical Oral Investigations 24, no. 7 (2019): 2385–93. http://dx.doi.org/10.1007/s00784-019-03097-3.

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Abstract Objectives The purpose of this study was to evaluate the clinical accuracy of virtual orthodontic setups by using a new CBCT-based approach. Materials and methods Ten patients who underwent pre-surgical orthodontics were included in this study. Pre-treatment and pre-surgical cone-beam CT (CBCT) scans and digital dental models were available. The pre-treatment digital dental model was used to create an orthodontic virtual setup. The digital dental models were fused with the corresponding CBCT scans, and the two CBCT scans were aligned using voxel-based matching. Moving each individual tooth from the virtual setup to the final outcome allows the calculation of the accuracy of the virtual setup by using an iterative closest point algorithm. Differences between virtual setup and final outcome were recorded as well as the ICC between two observers. Results The inter-observer variability showed a high level of agreement between the observers. The largest mean difference between observers was found in the cranial/caudal direction (0.36 ± 0.30 mm) and the roll rotation (1.54 ± 0.98°). Differences between the virtual setup and final outcome were small in the translational direction (0.45 ± 0.48 mm). Rotational mean differences were larger with the pitch of the incisors (0.00 ± 7.97°) and molars (0.01 ± 10.26°) as largest difference. Excessive extrusion of all upper teeth and more anterior movement than planned were seen for both upper and lower arch. Lower molars showed less extrusion. Clinical relevance The data of this study can be used to obtain more insight in the accuracy and achievability of orthodontic virtual setup. Tooth movement can now be studied in more details which can lead to new insights.

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5

Abedini, Vahid, Mohsen Shakeri, and Mohammad Hasan Siahmargouei. "Automatic Machining Setup Generation for Prismatic Components." Advanced Materials Research 445 (January 2012): 953–58. http://dx.doi.org/10.4028/www.scientific.net/amr.445.953.

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Computer aided process planning is the bridge between CAD and CAM. Setup planning is the major key to transform design concept into manufacturing domain, which is mainly experience based activity in modern manufacturing industry. Setup planning is a complicated non-linear task constrained by many factors such as tool approach direction, geometric feature relationship, fixturing constraint, tolerance requirement and manufacturing practice. Setup planning identifies which features must be machined in each setup and determines locating datum for each setup. This paper focuses on the development of a formalized procedure for automatic generation of feasible setups. For preventing of tolerance stack-up tried to use datum face as reference plane in fixture design. So, this paper presents a new method for setup planning with accurate respect to datum faces in design and machining. For the proposed work the authors have introduced two concepts namely, inferiority face and control face. A rule-based procedure in several steps is used for solving the problem. The system is developed in Visual Basic on a Solid Works platform. Trial runs with industrial parts indicate that the system is applicable for industrial use.

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6

Kannan, Sridhar, Ashish Kumar Singh, and Gaurav Gupta. "An edge over diagnostic setup." APOS Trends in Orthodontics 7 (December 1, 2017): 294–95. http://dx.doi.org/10.4103/2321-1407.219429.

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Diagnostic setup proposed by H.D. Kingsley serves as a practical aid in treatment planning and diagnosis. These setups have some inherent shortcomings. A simple technique of duplication of the setups in dental stone can solve problems encountered before as well as provide many other advantages over the conventional procedure. The diagnostic setup is prepared by the conventional method [Figure 1]. An alginate impression is then taken of the setups and poured in dental stone to obtain the derived treatment model [Figure 2]. The same setup can now be further modified for alternate lines of treatment. Subsequently models could then be obtained as required [Figure 3].

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7

Deja, Mariusz, and Mieczyslaw Siemiatkowski. "Generative Process Planning with Reasoning Based on Geometrical Product Specification." Key Engineering Materials 597 (December 2013): 159–64. http://dx.doi.org/10.4028/www.scientific.net/kem.597.159.

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The focus of this paper is on CAPP for parts manufacture in systems of definite process capabilities, involving the use of multi-axis machining centers for parts shaping and grinding machines for finishing. It presents in particular a decision making scheme for setup determination as a part of generative process planning. The planning procedure consists of two stages. The first stage is associated with generic setup determination applying tool accessibility analysis to machined features and reasoning based on geometrical product specification (GPS). The second stage involves machine specific setup planning considering the availability and capability of machines on a shop floor through setup merging. The impact of dimensional and geometric tolerance as well as the surface roughness of relatively complex mechanical element on the generated process plan with several setups was presented. The relevant reasoning mechanism within a decision making scheme on generated process alternatives is shown based on a numeric case.

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8

Huang, Samuel H. "Automated setup planning for lathe machining." Journal of Manufacturing Systems 17, no. 3 (1998): 196–208. http://dx.doi.org/10.1016/s0278-6125(98)80061-7.

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9

ZHANG‡, H. C., S. H. HUANG, and J. MEI. "Operational dimensioning and tolerancing in process planning: setup planning." International Journal of Production Research 34, no. 7 (1996): 1841–58. http://dx.doi.org/10.1080/00207549608905000.

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10

JONEJA, AJAY, and TIEN-CHIEN CHANG. "Setup and fixture planning in automated process planning systems." IIE Transactions 31, no. 7 (1999): 653–65. http://dx.doi.org/10.1080/07408179908969866.

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