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The Maker Movement and Its Influences on Technical Communication and Higher Learning
Published in Jason Chew Kit Tham, Design Thinking in Technical Communication, 2021
The Student Design Lab was a large workspace equipped with workbenches, tables, hand tools, some power tools, laser cutters, computers, and 3D printers. According to Guengerich, the primary purpose of this lab was to allow students to test out their design through rapid prototyping and modeling. It has open meeting pods with chairs and whiteboards that let students collaborate or discuss ideas. The Student Design Lab was open seven days a week during the regular semester. For welding and more intensive woodworking, students would need to use the Student Shop in the Civil Engineering building. This lab was a half-open workspace with 3D scanners, 3D printers, materials testing load frame, and woodwork facilities. The Student Shop was also open seven days a week during the semester. If students wanted to perform metalworks, they would need to use the Student Machine Shop in the Mechanical Engineering building. The machine shop was staffed by professional machinists with metalworking mills, lathes and grinders, milling machines, and waterjet cutters. Given the staffing hours, this lab was open only Monday through Friday during the regular semester.
Materials Selection in Precision Mechanical Design
Published in S.T. Smith, D.G. Chetwynd, Foundations of Ultraprecision Mechanism Design, 2017
The tables include a range of pure metals and alloys, but show few surprises. The common machine-shop metals, steels, aluminium alloys and brasses, are much used as structural materials in precision engineering. With the exception of the strength of hard steels they are generally indifferent performers across the whole range of groupings. They are used because high performance is not always needed, they are readily available and have low costs for materials or manufacturability. It is mildly surprising that neither aluminium nor copper alloys give good overall thermal performance, largely because of their high expansivity. The low density of aluminium is sometimes useful. The copper alloys also have rather high densities. However they are easy to work and still find a major role when non-magnetic structures are wanted. Bronzes and, particularly, beryllium copper perform well in the category most associated with spring design, Y/E, with other properties at best moderate for most precision applications of springs. Their common use for this purpose perhaps reflects both the unacceptability of steels (magnetic fields and corrosion may reduce repeatability) and the ease of providing thin sheets for ligament systems, for which the requirements are rather different to those for energy-storing spring applications. With careful heat treatment, hard beryllium copper may have a very finely distributed precipitate that rapidly arrests the motion under stress of crystal dislocations so that it makes very repeatable flexure hinges. This illustrates the limitation of numerically based selection methods, for it is difficult to quantify and tabulate such a property. Steel and cast iron, which also offers usefully high damping, still dominate for larger structures such as machine tools. Further details on thermal properties are given by Gitlin, 1955a.
Improvements in the thread cutting torque for a 6082-T6 aluminum-based alloy with tapping tools utilizing diamond coating
Published in Machining Science and Technology, 2018
Hannu Korhonen, Arto Koistinen, Reijo Lappalainen
Like diamond, also diamond-coated tool surface has superior abrasion resistance to all other materials. Thick diamond coatings, especially those deposited using CVD- and electrochemical techniques may also have quite rough surface after deposition. Rough tools have disadvantages for the further applications. In sliding contact they have higher friction and tend to rip the worked surface. Therefore it is essential to provide and maintain smooth tool faces and good cutting surfaces. In order to study this issue, the PVD-, CND-coated and uncoated reference tools were profiled with a surface roughness tester Mitutoyo Surftest SJ-301 (Mitutoyo Co., Kawasaki, Japan) using a diamond stylus with a tip radius of 2 µm. Especially rake face surfaces near a side cutting edges of the tools were compared in as-deposited state and after machine shop threading. Roughness tester was calibrated to meet the standards before each new measuring session. After positioning the tool to be measured so that a longitudinal direction along a flute channel can be evaluated, an arithmetic average Ra and a root mean square (RMS) Rq value of each specimen was measured 5 times. Values were determined using a Gaussian digital filter with a cut-off value of 0.25 mm, an arbitrary evaluation length of 1.25 mm, a measuring force of 0.75 mN and a stylus speed of 0.25 mm/s on the tool flute surface next to the rake face near the tool tip.
A column generation-based approach for proportionate flexible two-stage no-wait job shop scheduling
Published in International Journal of Production Research, 2020
Zhi Pei, Xuefang Zhang, Li Zheng, Mingzhong Wan
Job shop scheduling, as a classical branch of combinatorial optimisation problems, has been widely studied in recent literatures and is proved to be NP-hard (Garey and Johnson 1979). For a job shop scheduling problem (JSSP), there are jobs and machines , each job j includes several operations and each operation can be processed by only one machine. The route of each job j is fixed and known in advance, the goal is to find the order of the different jobs so as to optimise the target value. A special case of the JSSP forms when each job has equal processing time on different machines, and it is denoted as a proportionate job shop. Based upon the above notations, this paper considers a scheduling problem with a more complex structure, proportionate flexible job shop (PFJS), which combines the features of the proportionate job shop and the parallel machine shop (Labbi, Boudhar, and Oulamara 2017). A flexible job shop scheduling problem (FJSSP) is an extension of the classical JSSP that allows an operation to be processed by any machine from the same stage (Ortiz et al. 2018). In a PFJS, the stage S is defined as the largest number of operations each job contains, that is, a job has to go through at most S stages before its completion, and the processing time for each operation is equivalent. For a proportionate flexible job shop, there are m identical parallel machines at each stage. And the jobs could be processed on any one of the machines in that stage, given that the machine is not occupied and the job’s processing route contains that stage. For the PFJS problem discussed in the present paper, the preemption is not allowed.
Empowering manufacturing personnel through functional understanding
Published in Production Planning & Control, 2018
Ioannis Michalakoudis, Marco Aurisicchio, Peter Childs, Apollon Koutlidis, James Harding
Company’s figures for machine shop ‘scrap’ levels (Figure 10) and machine tool set-up/programming times (Figure 11) clearly indicate a considerable improvement occurring shortly after the training programme was complete, peaking at record values for the company approximately three months later, where the times eventually stabilised. Both sets of data show that the improvement in both waste (scrap) and set-up time reduction has dramatically exceeded our expectations of 15%.