A Study of the Effect of Combining Multi-Sensor Signals and Cutting Chip Color on Tool Life Prediction

Often, engineers with machining experience often judge machining state and tool life according to chips’ features. Engineers' experience is digitized in this study. During the cutting process, the cutting tool coming in contact with the workpiece produces a shear zone, which causes plastic deformation and shear slip. The chips closest to the shear zone can directly show the state of the tool and workpiece when the material is SKD61. This study used chip color, vibration, and current signal integration for prediction of machining state and cutting tool life. When the cutting tool wears increased, the chip surface color changed in the following way: purpleè purple blueè blue ècyan, or even green and yellow. When the cutting tool was in the accelerating wear phase, the color change was particularly obvious. The Back-Propagation Levenberg–Marquardt (BP-LM) predictive methodology was used to compare the predictive ability of voltage, vibration signal, and chip color. The Mean Absolute Percentage Error (MAPE) for the voltage signal was 12.28%, for the vibration signal it was 11.38%, and for the chip color combined with multi-sensor characteristics it was 7.85%. The MAPE of the chip color was the smallest. Using the General Regression Neural Network (GRNN) methodology, the MAPE for the voltage signal was 10.74%, for the vibration signal 7.96%, and for the chip color combined with multi-sensor characteristics was 6.59%. The MAPE of the chip color was the smallest. Obviously, the chip color combined with multi-sensor signals provided better predictive results than the vibration signal or voltage signal alone. There is currently no research on the usefulness of monitoring chip color for tool life prediction.

Tool Wear Prediction Using a Hybrid of Tool Chip Image and Evolutionary Fuzzy Neural Network

This paper proposed an evolutionary fuzzy neural network (EFNN) for tool wear prediction. The material chip is affected by cutting conditions during the cutting process. The different tool wear status causes different chip color which means the color of material chip can be an important factor for tool wear prediction. In this study, an industrial camera is used to capture chip image and convert it into CIE xy chromaticity features through a color conversion model. In addition, to improve the prediction accuracy, a dynamic group cooperative particle swarm optimization (DGCPSO) is proposed to optimize the EFNN parameters. The cutting time and CIE xy value are used as the input of the EFNN, and the output is predicted tool wear value. The experimental results show that the mean absolute percentage error (MAPE) of the proposed EFNN is 2.83% better than other methods.

Influence of Harvesting Date on Chemical Maturity for Processing Quality of Potatoes

The present study was conducted to find out a suitable harvesting date of processing potato varieties (Asterix, Courage and Lady Rosetta) from three different harvest dates [80, 90, and 100 days after planting (DAP) harvest] by chemical maturity monitoring. Eighty DAP harvest resulted the lowest mean total soluble sugar (TSS) (3.77 mg/g FW), reducing sugar (RS) (1.57 mg/g FW), sucrose (2.40 mg g-1 FW), fructose (0.77 mg/g FW) and polyphenol (238.94 μg/g FW) contents in all the varieties and at the same DAP harvest, dry matter (DM) content (21.71%) and chip color index (CCI) (0.67) remained at the lowest. Tubers harvested at 80 DAP produced good quality and acceptable colored processed products as it meets up the required processing quality, but lesser DM content might increase the cost of the product. Optimum DM content (24.07%) with moderate level of different sugar contents and acceptable CCI (1.13 to 1.85, <2.00) was found at 90 DAP harvest. Therefore, 90 DAP harvest could be considered as suitable harvesting date for processing by compromising some quality parameters (TSS, RS, sucrose, fructose and polyphenol contents). Among the varieties, Lady Rosetta and Courage were preferable for producing quality potato products. Highly significant and positive correlation existed between CCI and different chemical parameters. A strong correlation coefficient (r = 0.822**) and good fit (R2 = 0.6755) of the regression equation (CCI = 0.9341RS – 0.4969) between CCI and RS indicated that RS content played the vital role in the browning of the processed potato products. Ann. Bangladesh Agric. (2019) 23(2) : 89-103

Quantitative trait loci for starch-corrected chip color after harvest, cold storage and after reconditioning mapped in diploid potato

The objective of this study was to map the quantitative trait loci (QTLs) for chip color after harvest (AH), cold storage (CS) and after reconditioning (RC) in diploid potato and compare them with QTLs for starch-corrected chip color. Chip color traits AH, CS, and RC significantly correlated with tuber starch content (TSC). To limit the effect of starch content, the chip color was corrected for TSC. The QTLs for chip color (AH, CS, and RC) and the starch-corrected chip color determined with the starch content after harvest (SCAH), after cold storage (SCCS) and after reconditioning (SCRC) were compared to assess the extent of the effect of starch and the location of genetic factors underlying this effect on chip color. We detected QTLs for the AH, CS, RC and starch-corrected traits on ten potato chromosomes, confirming the polygenic nature of the traits. The QTLs with the strongest effects were detected on chromosomes I (AH, 0 cM, 11.5% of variance explained), IV (CS, 43.9 cM, 12.7%) and I (RC, 49.7 cM, 14.1%). When starch correction was applied, the QTLs with the strongest effects were revealed on chromosomes VIII (SCAH, 39.3 cM, 10.8% of variance explained), XI (SCCS, 79.5 cM, 10.9%) and IV (SCRC, 43.9 cM, 10.8%). Applying the starch correction changed the landscape of QTLs for chip color, as some QTLs became statistically insignificant, shifted or were refined, and new QTLs were detected for SCAH. The QTLs on chromosomes I and IV were significant for all traits with and without starch correction.

Tuber Yield, Water Productivity and Post-harvest Quality of Sprinkler-irrigated Chip Potato (solanum tuberosum L.) Under a Semiarid Climate

The potato chip industry has critical requirements regarding tuber physical and chemical aspects and these requirements are the characteristics targeted by chip potato breeding programs. This study aimed to evaluate 33 chip potato cultivars for the tuber yield and some physical and chemical characteristics of the tuber and potato chips at harvest and during cold storage period. Field experiments were conducted during the 2017 and 2018 growing seasons under sprinkler irrigation. Twenty-one cultivars were evaluated in 2017 and 22 cultivars were evaluated in 2018 using a randomized complete block design with four replications. The target traits under this study were tuber yield, tuber size, internal and external defects, sucrose and glucose content of the tuber and the chip color at harvest and during storage time. Fresh potato tuber yield varied with cultivar and ranged from 44.7 to 72.1 t/ha, averaging 58.5t/ha in 2017 and 60.8 t/ha in 2018. In 2017, cultivar NDTX081648CB-13W obtained the highest tuber yield and TX09396-1W obtained the lowest, while in 2018, Lamoka obtained the highest tuber yield and MSW044-1obtained the lowest. Cultivars NDTX081648CB-13W, MSW485-2, Atlantic, ACO1144-1W, and WANETA were the highest yielding cultivars in 2017, and Lamoka, HODAG, NICOLET, DAKOTA PEARL, and AF5429-3 were the highest yielding cultivars in 2018. Potato tuber size class of 4.7-8.75 cm was the most dominant and accounted for 93% in 2017 and 89% in 2018, respectively. Potato tuber specific gravity varied from 1.08-1.11 during both growing seasons and the dry matter content of the tubers ranged from 17.2 to 22.2% W9968-5 and MSV030-4 showed the highest internal defects of 47.2% and 33.7%, respectively, at harvest. W9968-5 still showed the highest external defects during the storage period. CO07070-13W, NDA081453CAB-2C and NY157 showed some internal defects during storage time in 2017. In 2018, NDA081453CAB-2C presented very high undesirable chip color (71.1%) followed by ND7519-1 (33.1%). In 2018, NDTX081648CB-13W, NY152 Niagara, and MSV313-2 showed relatively high internal defects (>15%) while Atlantic, MSV313-2, MSV358-3 and W9968-5 showed the highest external defects. During eight months of cold storage, NY162 showed 44.5% of external defects followed by MSV358-3 (24.6%), MSV313-2 (24%) and W9968-5 (20%). NY162 showed the highest total defects of 44.5% followed by MSV358-3, MSV313-2 and W9968-5 with total defects greater than 20%. Overall, there was a decrease in sucrose contents in the tubers after six months of cold storage except for the cultivars AF5040-8 and NDA081453CAB-2C. It increased thereafter during eight months in cold storage. However, sucrose content of the tubers at the end of the storage period was lower than the sucrose content at harvest except for B2727-2, NDA081453CAB-2C, NDTX081648CB-13W, and CO07070-13W. Significantly 100% increase in sucrose content in tubers of AF5040-8, DAKOTA PEARL, MSW485-2 Huron, MSX540-4 Mackinaw, NDA081453CAB-2C, and NDTX081648CB-13W was observed during the storage period. Glucose content of tubers changed during the storage period and was more noticeable in AF5040-8, AF5040-8, DAKOTA PEARL, MSW485-2 Huron, MSX540-4 Mackinaw, ND7519-1, NDA081453CAB-2C, and NDTX081648CB-13W. There was considerable increase in glucose content in ACO1144-1W, NDA081453CAB-2C, NDTX081648CB-13W, CO07070-13W, and W9968-5 tubers. At nine-month storage period, only Lamoka, ACO1144-1W, AF5040-8, MSX540-4, and CO02321-4W, HODAG, MSV030-4, MSW044-1, NY152 Niagara, NY162, and WANETA HODAG showed nice chip color. NDA081453CAB-2C, NDTX081648CB-13W, ND7519-1, and NDA081453CAB-2C presented the least desirable chip color with score “5”. Cultivars with consistent scores of “1” constitute promising lines for chip potato producers across the dry and hot environment of the southwest region of the United States.