milling production line mapping

a graphical method for performance mapping of machines and milling tools - sciencedirect

Optimal design of the machining setup in terms of installed machines, cutting tools and process parameters is of paramount importance for every manufacturing company. In most of the metal cutting companies, all choices related to machine eligibility and cutting parameters selection typically come from heuristic approaches and follow supplier indications or base on the skill of experienced machine operators. More advanced solutions, such as model-based and virtual approaches, are adopted less frequently mainly due to the lack of these techniques in grasping the underlying knowledge successfully. Aim of this work is to introduce a synthetic graphical representation of machining centers and cutting tools capabilities, to provide an accessible way to evaluate the feasibility and close-to-limit conditions of the cutting process. Taking inspiration from previous scientific works from the measurement engineering field, a set of 2D and 3D graphs are presented to map machine, tools and process capabilities, as well as their obtainable manufacturing performances and expectable tool life. This approach synthesizes the nominal data coming from different sources (catalogues, database, tool model geometries etc.) and the real cutting tools parameters used during the production phase. Some examples are provided to show the potential of this graphical evaluation in supporting process planning and decision-making and in formalizing the machining setup knowledge. Further developments are devoted to extend the method to other manufacturing processes, including hybrid processes. At the same time, an in-process data gathering software will be integrated for building a solid database that can be used by an autonomous multi-technological process selector, as well as by a pre-process condition advisor in an Industry 4.0 oriented way.

tool condition monitoring techniques in milling process a review - sciencedirect

The most important improvement in metal the cutting industry is the continuous utilization of cutting tools and tool condition monitoring system. In the metal cutting process, the tool condition has to be administered either by operators or by online condition monitoring systems to prevent damage to both machine tools and workpiece. Online tool condition monitoring system is highly essential in modern manufacturing industries for the rising requirements of cost reduction and quality improvement. This paper summaries various monitoring methods for tool condition monitoring in the milling process that have been practiced and described in the literature.

mapping qtl main and interaction influences on milling quality in elite us rice germplasm | springerlink

Rice (Oryza sativa L.) head-rice yield (HR) is a key export and domestic quality trait whose genetic control is poorly understood. With the goal of identifying genomic regions influencing HR, quantitative-trait-locus (QTL) mapping was carried out for quality-related traits in recombinant inbred lines (RILs) derived from crosses of common parent Cypress, a high-HR US japonica cultivar, with RT0034, a low-HR indica line (129 RILs) and LaGrue, a low-HR japonica cultivar (298 RILs), grown in two US locations in 20052007. Early heading increased HR in the Louisiana (LA) but not the Arkansas (AR) location. Fitting QTL-mapping models to separate QTL main and QTLenvironment interaction (QEI) effects and identify epistatic interactions revealed six main-effect HR QTLs in the two crosses, at four of which Cypress contributed the increasing allele. Multi-QTL models accounted for 0.36 of genetic and 0.21 of geneticenvironment interaction of HR in MY1, and corresponding proportions of 0.25 and 0.37 in MY2. The greater HR advantage of Cypress in LA than in AR corresponded to a genomewide pattern of opposition of HR-increasing QTL effects by AR-specific effects, suggesting a selection strategy for improving this cultivar for AR. Treating yearlocation combinations as independent environments resulted in underestimation of QEI effects, evidently owing to lower variation among years within location than between location. Identification of robust HR QTLs in elite long-grain germplasm is suggested to require more detailed attention to the interaction of plant and grain development parameters with environmental conditions than has been given to date.

Bauer A, Hoti F, von Korff M, Pillen K, Lon J, Sillanp M (2009) Advanced backcross-QTL analysis in spring barley (H. vulgare ssp. spontaneum) comparing a REML versus a Bayesian model in multi-environmental field trials. Theor Appl Genet 119:105123

Boer MP, Wright D, Feng L, Podlich DW, Luo L, Cooper M, van Eeuwijk FA (2007) A mixed-model quantitative trait loci (QTL) analysis for multiple-environment trial data using environmental covariables for QTL-by-environment interactions, with an example in maize. Genetics 177:18011813

Counce PA, Bryant RJ, Bergman CJ, Bautista RC, Wang YJ, Siebenmorgen TJ, Moldenhauer KAK, Meullenet JFC (2005) Rice milling quality, grain dimensions, and starch branching as affected by high night temperatures. Cereal Chem 82:645648

Fan CH, Xing YZ, Mao HL, Lu TT, Han B, Xu CG, Li XH, Zhang QF (2006) GS3, a major QTL for grain length and weight and minor QTL for grain width and thickness in rice, encodes a putative transmembrane protein. Theor Appl Genet 112:11641171

Fjellstrom RG, Chen M, Bergman CJ, McClung AM (2004) Single nucleotide polymorphism markers at the rice alk locus controlling alkali spreading value. In: Rice Technical Working Group Meeting. Rice Technical Working Group, New Orleans, LA, p 66

Fukuta Y, Sasahara H, Tamura K, Fukuyama T (2000) RFLP linkage map included the information of segregation distortion in a wide-cross population between indica and japonica rice (Oryza sativa L.). Breed Sci 50:6572

Harushima Y, Yano M, Shomura A, Sato M, Shimano T, Kuboki Y, Yamamoto T, Lin SY, Antonio BA, Parco A, Kajiya H, Huang N, Yamamoto K, Nagamura Y, Kurata N, Khush GS, Sasaki T (1998) A high-density rice genetic linkage map with 2275 markers using a single F2 population. Genetics 148:479494

Jiang GH, Hong XY, Xu CG, Li XH, He YQ (2005) Identification of quantitative trait loci for grain appearance and milling quality using a doubled-haploid rice population. J Integr Plant Biol 47:13911403

Li ZK, Yu SB, Lafitte HR, Huang N, Courtois B, Hittalmani S, Vijayakumar CHM, Liu GF, Wang GC, Shashidhar HE, Zhuang JY, Zheng KL, Singh VP, Sidhu JS, Srivantaneeyakul S, Khush GS (2003b) QTLenvironment interactions in rice. I. Heading date and plant height. Theor Appl Genet 108:141153

Li JM, Xiao JH, Grandillo S, Jiang LY, Wan YZ, Deng QY, Yuan LP, McCouch SR (2004) QTL detection for rice grain quality traits using an interspecific backcross population derived from cultivated Asian (O. sativa L.) and African (O. glaberrima S.) rice. Genome 47:697704

Lin SY, Ikehashi H, Yanagihara S, Kawashima A (1992) Segregation distortion via male gametes in hybrids between indica and japonica or wide-compatibility varieties of rice (Oryza sativa L). Theor Appl Genet 84:812818

Lin HX, Yamamoto T, Sasaki T, Yano M (2000) Characterization and detection of epistatic interactions of 3 QTLs, Hd1, Hd2, and Hd3, controlling heading date in rice using nearly isogenic lines. Theor Appl Genet 101:10211028

Maccaferri M, Sanguineti MC, Corneti S, Ortega JLA, Salem MB, Bort J, DeAmbrogio E, del Moral LFG, Demontis A, El-Ahmed A, Maalouf F, Machlab H, Martos V, Moragues M, Motawaj J, Nachit M, Nserallah N, Ouabbou H, Royo C, Slama A, Tuberosa R (2008) Quantitative trait loci for grain yield and adaptation of durum wheat (Triticum durum Desf.) across a wide range of water availability. Genetics 178:489511

McCouch SR, Teytelman L, Xu YB, Lobos KB, Clare K, Walton M, Fu BY, Maghirang R, Li ZK, Xing YZ, Zhang QF, Kono I, Yano M, Fjellstrom R, DeClerck G, Schneider D, Cartinhour S, Ware D, Stein L (2002) Development and mapping of 2240 new SSR markers for rice (Oryza sativa L.). DNA Res 9:199207

Septiningsih EM, Trijatmiko KR, Moeljopawiro S, McCouch SR (2003) Identification of quantitative trait loci for grain quality in an advanced backcross population derived from the Oryza sativa variety IR64 and the wild relative O. rufipogon. Theor Appl Genet 107:14331441

Shimomura K, Low-Zeddies SS, King DP, Steeves TDL, Whiteley A, Kushla J, Zemenides PD, Lin A, Vitaterna MH, Churchill GA, Takahashi JS (2001) Genome-wide epistatic interaction analysis reveals complex genetic determinants of circadian behavior in mice. Genome Res 11:959980

Siebenmorgen TJ, Meullenet JF (2004) Impact of drying, storage, and milling of rice quality and functionality. In: Champagne ET (ed) Rice: chemistry and technology, 3rd edn. The American Association of Cereal Chemists, St. Paul, pp 301328

Tan YF, Sun M, Xing YZ, Hua JP, Sun XL, Zhang QF, Corke H (2001) Mapping quantitative trait loci for milling quality, protein content and color characteristics of rice using a recombinant inbred line population derived from an elite rice hybrid. Theor Appl Genet 103:10371045

Wan XY, Wan JM, Weng JF, Jiang L, Bi JC, Wang CM, Zhai HQ (2005) Stability of QTLs for rice grain dimension and endosperm chalkiness characteristics across eight environments. Theor Appl Genet 110:13341346

Wang GL, Mackill DJ, Bonman JM, McCouch SR, Champoux MC, Nelson RJ (1994) RFLP mapping of genes conferring complete and partial resistance to blast in a durably resistant rice cultivar. Genetics 136:14211434

Xing YZ, Tan YF, Hua JP, Sun XL, Xu CG, Zhang Q (2002) Characterization of the main effects, epistatic effects and their environmental interactions of QTLs on the genetic basis of yield traits in rice. Theor Appl Genet 105:248257

Yamamoto T, Taguchi-Shiobara F, Ukai Y, Sasaki T, Yano M (2001) Mapping quantitative trait loci for days-to-heading, and culm, panicle and internode lengths in a BC1F3 population using an elite rice variety, Koshihikari, as the recurrent parent. Breed Sci 51:6371

Yano M, Harushima Y, Nagamura Y, Kurata N, Minobe Y, Sasaki T (1997) Identification of quantitative trait loci controlling heading date in rice using a high-density linkage map. Theor Appl Genet 95:10251032

Yoshida S, Ikegami M, Kuze J, Sawada K, Hashimoto Z, Ishii T, Nakamura C, Kamijima O (2002) QTL analysis for plant and grain characters of sake-brewing rice using a doubled haploid population. Breed Sci 52:309317

Zhao K, Wright M, Kimball J, Eizenga G, McClung A, Kovach M, Tyagi W, Ali ML, Tung CW, Reynolds A, Bustamante CD, McCouch SRP (2010) Genomic diversity and introgression in O. sativa reveal the impact of domestication and breeding on the rice genome. PLoS One (in press)

Zheng TQ, Xu JL, Li ZK, Zhai HQ, Wan JM (2007) Genomic regions associated with milling quality and grain shape identified in a set of random introgression lines of rice (Oryza sativa L.). Plant Breed 126:158163

We thank J. Delgado for all image analysis measurements; J. Cammack, K. Landry, C. Henry, P. Roberts, J. Bonnette, H. Hoffpauir, C. Conner, and J. Vawter for all milling determinations; N. Gipson for amylose content determinations; L. Murray for consultation on linear models; E. Christensen and S. Simpson for genotypic analysis; I. Roughton for fissuring determinations; and F.-M. Xie for providing the MY1 mapping population. Support for this work has been provided in part by US Department of Agriculture Cooperative State Research, Education and Extension ServiceNational Research InitiativeApplied Plant Genomics Program grant 2004-35317-14867 entitled RiceCAP: A coordinated research, education, and extension project for the application of genomic discoveries to improve rice in the United States. This is contribution 09-002-J from the Kansas Agriculture Experiment Station.

Nelson, J.C., McClung, A.M., Fjellstrom, R.G. et al. Mapping QTL main and interaction influences on milling quality in elite US rice germplasm. Theor Appl Genet 122, 291309 (2011). https://doi.org/10.1007/s00122-010-1445-z

mapping quantitative trait loci for milling quality, protein content and color characteristics of rice using a recombinant inbred line population derived from an elite rice hybrid | springerlink

Milling properties, protein content, and flour color are important factors in rice. A marker-based genetic analysis of these traits was carried out in this study using recombinant inbred lines (RILs) derived from an elite hybrid cross Shanyou 63, the most-widely grown rice hybrid in production in China. Correlation analysis shows that the traits were inter-correlated, though the coefficients were generally small. Quantitative trait locus (QTL) analysis with both interval mapping (IM) and composite interval mapping (CIM) revealed that the milling properties were controlled by the same few loci that are responsible for grain shape. The QTL located in the interval of RM42-C734b was the major locus for brown rice yield, and the QTL located in the interval of C1087-RZ403 was the major locus for head rice yield. These two QTLs are the loci for grain width and length, respectively. The Wx gene plays a major role in determining protein content and flour color, and is modified by several QTLs with minor effect. The implications of the results in rice breeding were discussed.

Tan, Y., Sun, M., Xing, Y. et al. Mapping quantitative trait loci for milling quality, protein content and color characteristics of rice using a recombinant inbred line population derived from an elite rice hybrid. Theor Appl Genet 103, 10371045 (2001). https://doi.org/10.1007/s001220100665