Digital twin control of multi-axis wood CNC machining center based on LinuxCNC

Abstrack: This paper presents an application of an open architecture control system implemented on a multi-axis wood computer numerical control milling machining center, as a digital twin control. The development of the digital twin control system was motivated by research and educational requirements, especially in the field of configuring a new control system by “virtual commissioning”, enabling the validation of the developed controls, program verification, and analysis of the machining process and monitoring. The considered wood computer numerical control (CNC) machining system is supported by an equivalent virtual machine in a computer-aided design and computer-aided manufacturing (CAD/CAM) environment, as well as in the control system, as a digital twin. The configured virtual machines are used for the verification of the machining program and programming system via machining simulation, which is extremely important in multi-axis machining. Several test wood workpieces were machined to validate the effectiveness of the developed control system based on LinuxCNC

USING PROC NLMIXED TO ANALYZE A TIME OF WEED REMOVAL STUDY

Many studies in weed science involve fitting a nonlinear model to experimental data. Examples of such studies include dose-response experiments and studies to determine the critical period of weed control. The experiments typically use block designs and often have additional complexity such as split-plot features. However, nonlinear models are typically fit using software such as SAS PROC NLIN that are limited to a single error term and whose ability to account for blocking is either awkward or lacking entirely. For example, Seefeldt et al. (1995) only proceeded in fitting the nonlinear model after establishing that the block effect was negligible. Issues such as multiple error terms in split-plot designs are simply not dealt with at all. In this paper, we examine a weed removal study carried out as a split-plot design with blocks and illustrate the use of SAS PROC NLMIXED to account for blocks and the two-level error structure

Early-season insect defoliation influences the critical time for weed removal in soybean

To develop more effective pest-management strategies, it is essential to understand how different pests interact with each other and the crop. Field studies were conducted in 2003 and 2004 at two Nebraska locations to determine the effects of early-season crop defoliation on the critical time for weed removal (CTWR) in narrow-row soybean. Three soybean defoliation levels were selected to simulate 0, 30, and 60% leaf tissue removal by the bean leaf beetle. Weeds were allowed to compete with the crop until V2, V4, V6, R3, and R5 growth stages. There were also season-long weedy and weed-free treatments. Results indicated that the CTWR in soybean occurred earlier as defoliation levels increased from 0 to 60%. The CTWR occurred at V3, V2, and V1 growth stage for 0, 30, and 60% defoliation levels, respectively. Overall, 60% defoliation resulted in earlier CTWR by at least 14 d. Yield losses from defoliation and weed interference were primarily associated with a reduction in number of pods per plant-1

MACROS AS A PROGRAMMING TOOL FOR SYNCHRONIZATION OF TWO NON‐SYNCHRONIZABLE INDUSTRIAL ROBOTS

The main goal of this paper was to connect two controllers of the older generation into one robotic cell, then software implements their synchronized work on servicing and welding certain objects. Two controllers manufactured by Yaskawa Motoman were used with the associated manipulators. The hardware solution involved connecting the controllers via General I/O circuit board. The software solution involved parallel programming of two robots for synchronized operation on a common task. During programming, it was necessary to create macro jobs that implemented repetitive actions, such as calling and waiting for robots, grabbing and releasing objects, as well as the actions of starting and stopping the program. The conclusion of presented research is that the robotic cell, formed by two robots that are not intended for synchronization, meets the requirements that until now could only be solved with robots of the newer generation. Proposed solution was confirmed by experimental verification

EC02-173 Spotted and Diffuse Knapweed

Spotted knapweed (Centaure amaculosa Lam. = C. biebersteinii DC.) and diffuse knapweed (C.diffusa Lam.) are two of Nebraska’s seven noxious weeds. They are also noxious in at least 17 other states. These are closely related species that are well adapted to a variety of habitats including open forests, rangelands and pastures, Conservation Reserve Program lands, roadsides, and ditch banks. Centaurea is a large genus of over 400 species, 32 of which are common weeds of the United States and several of which [e.g., yellowstar thistle, C. solstitalis L, and Russian knapweed, C. repens L. =Acroptilon repens (L.) DC.] have been identified officially as noxious weeds in nearby western states. Other Centaurea species areused as ornamentals. The knapweeds were introduced to the United States from the grasslands of southeastern Europe and Asia. Spotted knapweed now infests more than seven million acres and diffuse knapweed more than three million acres of rangeland and pastures in the western United States

EC02-173 Spotted and Diffuse Knapweed

Spotted knapweed (Centaure amaculosa Lam. = C. biebersteinii DC.) and diffuse knapweed (C.diffusa Lam.) are two of Nebraska’s seven noxious weeds. They are also noxious in at least 17 other states. These are closely related species that are well adapted to a variety of habitats including open forests, rangelands and pastures, Conservation Reserve Program lands, roadsides, and ditch banks. Centaurea is a large genus of over 400 species, 32 of which are common weeds of the United States and several of which [e.g., yellowstar thistle, C. solstitalis L, and Russian knapweed, C. repens L. =Acroptilon repens (L.) DC.] have been identified officially as noxious weeds in nearby western states. Other Centaurea species areused as ornamentals. The knapweeds were introduced to the United States from the grasslands of southeastern Europe and Asia. Spotted knapweed now infests more than seven million acres and diffuse knapweed more than three million acres of rangeland and pastures in the western United States

Pollen-mediated gene flow from herbicide-resistant yellow corn to non-genetically engineered food-grade white corn

Nebraska is the number one producer of food-grade white corn in the United States. Pollen-mediated gene flow (PMGF) from genetically engineered high alpha-amylase corn, known as Enogen corn, to food-grade white corn can have undesirable outcomes. Alpha-amylase can convert starch in white corn to sugar during or after its processing, degrading the quality of processed products. Thus, proximity to Enogen corn puts white corn production at risk. The objectives of this study were to evaluate the PMGF from herbicide-resistant yellow corn to food-grade white corn and assess the significance of wind speed and direction. Field experiments were set up using a Nelder-wheel design in 2021 and 2022 in Nebraska, with yellow field corn as pollen donor in the center and white corn surrounding it as pollen receptor. At the end of the season, samples of white corn cobs were collected up to 50 and 70 m from four cardinal and ordinal directions, respectively. PMGF was detected by counting the number of yellow kernels on the white cobs. More than 4 million kernels were screened and the highest frequency of PMGF (0.0621–0.1950) was detected at the nearest distance (1 m). PMGF decreased exponentially with distance; however, it was still observed (0.0020–0.0032) at the greatest distance (70 m) evaluated in this study. Wind profile played a significant role in PMGF. Wind frequency (r = 0.58 ≤ 0.86) and wind run (r = 0.36 ≤ 0.95) were moderately to strongly correlated with PMGF in 2021 and 2022, respectively. The results are concerning for white corn growers due to the coexistence of Enogen corn and food-grade white corn