食品攪拌機結構設計【含圖紙】

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畢業(yè)設計開題報告 題 目： 食品攪拌機結構設計 院 （系）： 應用科技學院 專 業(yè)： 機械設計制造及其自動化 班 級： 07011204 學 號： 0701120404 姓 名： 李雪梅 指導教師： 李銳鋒 填表日期： 2011 年 01 月 20 日 畢業(yè)設計（論文）開題報告 1.本課題的研究內容、重點及難點 一.主要內容 1. 參觀調研，查閱資料。到相關企業(yè)調研，了解如何對一個產品進行結構設計。結合本課題，查閱相關資料； 2. 進行市場調查，了解現(xiàn)有攪拌機結構與工作原理，做好設計前的準備工作； 3. 明確設計要求，分析攪拌機的設計可能性和經濟性等因素，完成相關結構與零件設計； 4. 設計的零件結構要求完整、合理； 5. 完成攪拌裝置的結構的總體尺寸設計和結構草圖的繪制； 6. 合理選擇相關組件，進行傳動系統(tǒng)的設計和相關計算； 7. 合理選用零件的材料，編制主要零件的制造工藝； 8. 完善設計，繪制零件圖，繪制總裝配圖，標注技術要求； 9. 撰寫畢業(yè)設計（論文）說明書； 10. 翻譯專業(yè)外語獻 二.重點難點 1. 設計、選擇合適的攪拌和容器轉盆機構件尺寸，基于桿組法計算并編制程序完成攪拌機的兩個動作協(xié)調運動仿真； 2. 根據(jù)所選構件尺寸，計算分析并校核各構件強度； 3. 使用三維造型軟件，完成該攪拌機的三維造型，生成三維渲染圖和線框圖、二維裝配圖和關鍵零部件圖； 4. 編寫設計說明書，詳細說明設計思路和計算分析過程； 2.準備情況（已查閱的參考文獻或進行的調研） 一.研究背景 飲食水平是一個國家文明程度和人民生活質量高低的重要標志。食品的質量和供應狀況，直接關系著全民族的體質，影響到國家的政治安定和社會進步。世界上經濟發(fā)達的國家都十分重視發(fā)展食品工業(yè)。中國食品工業(yè)負有滿足人民日益增長的物質文化生活需要和為國家經濟建設提供積累的雙重任務，是國民經濟的重要組成部分。發(fā)展食品工業(yè)可以加速農業(yè)結構及其產品品質的優(yōu)化調整，提高農產品經濟價值，促進農業(yè)生產的良性循環(huán)。同時，對于帶動和促進飼料工業(yè)、包裝機械工業(yè)、機械工業(yè)、電子工業(yè)和精細化學工業(yè)等相關行業(yè)協(xié)調發(fā)展，適應餐飲業(yè)，旅游業(yè)等第三產業(yè)崛起的需要，繁榮城鄉(xiāng)市場，擴大外貿出口以及擴大勞動就業(yè)等都具有十分重要的作用。80年代以來，中央和地方都十分重視食品工業(yè)的發(fā)展，制定了一系列支持食品工業(yè)發(fā)展的政策。同時，國務院制定了“90年代中國食物結構發(fā)展與改革綱要”中國食品工業(yè)協(xié)會制定了“九五中國食品工業(yè)科技發(fā)展綱要”。河南省食品工業(yè)經過20多年的快速發(fā)展，各項指標已走在中國的前列，尤其是作為一個農業(yè)大省，在調整經濟結構、推進農業(yè)產業(yè)化進程中，大力發(fā)展食品工業(yè)更是具有重要的意義。因此，在剛剛結束的省人代會上把以畜產品加工、糧油加工、果蔬加工為主體的食品工業(yè)做為第一大支柱產業(yè)來培育。目前，中國食品工業(yè)已初步形成門類比較齊全、技術不斷進步、產品日益豐富、運銷網(wǎng)絡通暢的生產經營體系，成為國民經濟中處于重要戰(zhàn)略地位的一大產業(yè)。年產值5400多億元。在中國各工業(yè)門類中，產值第一。 由上可知，食品機械在國民經濟中的地位是如此之高。攪拌機在生活中的應用相當?shù)膹V泛，攪拌水果，奶油，得出的味道爽口，還可以攪拌蛋糕液，餡料、打蛋及和制面團，特別在酒家、飯店、面包屋以及食品廠家等作攪拌食料，揉和面團之用，是生產優(yōu)質糕點的理想設備。因此設計一個合理的攪拌機是非常的必要。 二.參考文獻 ［1］ 孫恒編. 機械原理 . 北京 ：高教出版社 , 2002.4 ［2］ 廖漢元，孔建益．機械原理．北京：機械工業(yè)出版社，2008 ［3］ 濮良貴. 機械設計. 北京: 高教出版社 , 2002.1 ［4］ 陳國華編著.機械機構及應用.北京：機械工業(yè)出版社，2008 ［5］ 周開勤. 機械零件手冊. 北京: 高教出版社 , 2001.7 ［6］ 朱張嬌. 工程材料. 北京: 清華大學出版社,2004.7 ［7］ 楊好學. 互換性與技術測量. 西安: 西安電子科技大學出版社,2006.2 ［8］ 王大康. 機械設計基礎.北京：機械設計出版社，2003 ［9］ 董玉紅. 數(shù)控技術．北京：高等教育出版社，2008 ［10］劉國慶等編.AutoCAD 2004基礎教程[M]．北京：清華大學出版社，2003 ［11］劉竹清編.Pro/E Wildfire實用教程[M]．中國鐵道出版社，2004 ［12］Chin Fu Tsang, Thomas Buscheck, Christine Doughty. Aquifer thermal energy storage: a numerical simulation of Auburn university field experiments. Water resource research, vo1.17,No. 3, June 2000 ［13］ Sergison, J. Wicks, F. Mulligan, G Becker, M. Yerazunis, S. System Evaluation of Heat Pumps Operated in Both Heating and Air Conditioning Modes;Volume PAS-99, Issue 3, May 2000 三.現(xiàn)有設備 計算機一臺；使用軟件為Pro/Engineer3.0；Auto CAD2007；設備齊全。 畢業(yè)設計（論文）開題報告 3.實施方案、進度實施計劃及預期提交的畢業(yè)設計資料 一.實施方案、進度實施計劃 1. 2011年1月15日至2011年1月20日，理解消化課題，明確設計要求收集資料文獻，根據(jù)課題內容完成開題報告； 2. 2011年3月1日至3月11日，進行市場調查，了解現(xiàn)有攪拌機裝置的結構與工作原理，做好設計前的準備工作，初步完成譯文翻譯； 3. 2011年3月11日至3月21日，查閱資料，完成攪拌機的結構的總體尺寸設計； 4. 2011年3月21日至4月1日，完成結構草圖的繪制和零件工作圖的設計繪制等； 5. 2011年4月1日至4月11日，進行各部分的運動和受力，完成相關組件的計算； 6. 2011年4月11日至4月21日，編制主要零件的制造工藝，完成英文翻譯； 7. 2011年4月21日至5月11日，合理選用零件的材料，繪制零件圖和裝配圖，標注技術要求； 8. 2011年5月11日至5月21日，完善設計，撰寫論文； 9. 2011年5月21日至5月29日，完成畢業(yè)設計，修改并打印論文。 二.預期提交的畢業(yè)設計資料 設計說明書，圖紙。 指導教師意見 指導教師： 年 月 日 開題小組意見 開題小組成員簽字： 年 月 日 院系審核意見 院系主管領導簽字： 年 月 日 桂林電子科技大學畢業(yè)設計報告（論文）用紙 編號： 畢業(yè)設計(論文)外文翻譯 （原文） 院 （系）： 應用科技學院 專 業(yè)： 機械設計及其自動化 學生姓名： 李雪梅 學 號： 0701120404 指導教師單位： 應用科技學院 姓 名： 李銳鋒 職 稱： 講師 2011年 6 月 12 日 18 New Manufacturing Technologies INTRODUCTION Driven by international competition and aided by application of computer technology, manufacturing firms have been pursuing two principal approaches during the 1980's: * automation, and * integration. Automation is the substitution of machine for human function; integration is the reduction or elimination of buffers between physical or organizational entities. The strategy behind manufacturing firms' application of new automation technologies is multidimensional: * to liberate human resources for knowledge work, * to eliminate hazardous or unpleasant jobs, * to improve product uniformity, and * to reduce costs and variability. The execution of that strategy has lead firms automate away simple, repetitive, or unpleasant functions in their offices, factories, and laboratories. Integration, when used as an approach to improve quality, cost, and responsiveness to customers, requires that firms find ways to reduce physical, temporal, and organizational barriers among various functions. Such buffer reduction has been implemented by the elimination of waste, the substitution of information for inventory, the insertion of computer technology, or some combination of these. In most process industries - oil refining and papermaking, for example - automation and integration have been critical trends for decades. However, in discrete goods manufacture - electronics and automobiles, for example - significant movement in these directions is a recent phenomenon in the United States. This chapter defines, examines, and illustrates the application of technologies that support the trends toward more automation and integration in discrete goods manufacturing. We begin with a discussion of the technological hardware and software that has been evolving. We then look at six management challenges that must be addressed to support these trends. And, finally, we look at the issue of economic evaluation the new technologies. AUTOMATION IN MANUFACTURING As characterized, for example, by Toshiba, in their OME Works facility, automation in manufacturing can be divided into three categories: *factory automation, *engineering automation, and *planning and control automation. Automation in these three areas can occur independently, but coordination among the three, as is being pursued by this Toshiba facility, drives opportunities for computer integrated manufacturing, discussed below. Factory Automation Although software also plays a critical role, factory automation is typically described by the technological hardware used in manufacturing: robots, numerically controlled (NC) machine tools, and automated material handling systems. Increasingly, these technologies are used in larger, integrated systems, known as manufacturing cells or flexible manufacturing systems (FMS). The term robot refers to a piece of automated equipment, typically programmable, that can be used for moving material to be worked on (pick and place) or assembling components into a larger device. Robots are also used to substitute for direct human labor in the use of tools or equipment, as is done, for example, by a painting robot, or a welding robot, which both positions the welder and welds joints and seams. Robots can vary significantly in complexity, from simple single-axis programmable controllers to sophisticated multi-axis machines with microprocessor control and real-time, closed-loop feedback and adjustment. A numerically-controlled (NC) machine tool is a machine tool that can be run by a computer program that directs the machine in its operations. A stand-alone NC machine needs to have the workpieces, tools, and NC programs loaded and unloaded by an operator. However, once an NC machine is running a program on a workpiece, it requires significantly less operator involvement than a manually operated machine. A CNC (computer numerically-controlled) machine tool typically has a small computer dedicated to it, so that programs can be developed and stored locally. In addition, some CNC tools have automated parts loading and tool changing. CNC tools typically have real-time, on-line program development capabilities, so that operators can implement engineering changes rapidly. A DNC (distributed numerically-controlled) system consists of numerous CNC tools linked together by a larger computer system that downloads NC programs to the distributed machine tools. Such a system is necessary for the ultimate integration of parts machining with production planning and scheduling. Automated inspection of work can also be realized with, for example, vision systems or pressure-sensitive sensors. Inspection work tends to be tedious and prone to errors, especially in very high volume manufacturing settings, so it is a good candidate for automation. However, automated inspection (especially with diagnosis capability) tends to be very difficult and expensive. This situation, where automated inspection systems are expensive to develop, but human inspection is error-prone, demonstrates the value of automated manufacturing systems with very high reliability: In such systems, inspection and test strategies can be developed to exploit the high-reliability features, with the potential to reduce significantly the total cost of manufacture and test. Automated material handling systems move workpieces among work centers, storage locations, and shipping points. These systems may include autonomous guided vehicles, conveyor systems, or systems of rails. By connecting separate points in the production system, automated material handling systems serve an integration function, reducing the time delays between different points in the production process. These systems force process layout designers to depict clearly the path of each workpiece and often make it economical to transport workpieces in small batches, providing the potential for reduced wait times and idleness. A flexible manufacturing system (FMS) is a system that connects automated workstations with a material handling system to provide a multi-stage automated manufacturing capability for a wider range of parts than is typically made on a highly-automated, non-flexible, transfer line. These systems provide flexibility because both the operations performed at each work station and the routing of parts among work stations can be varied with software controls. The promise of FMS technology is to provide the capability for flexibility approaching that available in a job shop with equipment utilizations approaching what can be achieved with a transfer line. In fact, a FMS is a technology intermediate to these two extremes, but good management can help in pushing both frontiers simultaneously. Automated factories can differ significantly with respect to their strategic purpose and impact. Two examples, Matsushita and General Electric, may be instructive. In Osaka, Japan, Matsushita Electric Industrial Company has a plant that produces video cassette recorders (VCRs). The heart of the operation features a highly automated robotic assembly line with 100-plus work stations. Except for a number of trouble-shooting operators and process improvement engineers, this line can run, with very little human intervention, for close to 24 hours per day, turning out any combination of 200 VCR models. As of August 1988, the facility was underutilized; Matsushita was poised to increase production, by running the facility more hours per month, as demand materialized. In this situation, the marginal cost of producing more output is very low. Matsushita has effectively created a barrier to entry in the VCR industry, making it very difficult for entrants to compete on price. The second example is General Electric's Aircraft Engine Group Plant III, in Lynn, Massachusetts. This fully automated plant machines a small set of parts used by the Aircraft Engine Group's assembly plant. In contrast to Matsushita's plant, which provides strategic advantage in the VCR product market, the strategic advantage provided by GE's plant seems to address its labor market. Plant III's investment is now sunk. Eventually, it will run around the clock at very high utilization rates with a very small crew. As volume is ramped up, GE has the ability to use Plant III's capacity and cost structure as leverage with its unionized labor force which is currently making many of the parts that could eventually be transferred to Plant III. Thus, factory automation can address a variety of types of strategic needs, from product market considerations to labor market concerns. Engineering Automation From analyzing initial concepts to finalizing process plans, engineering functions that precede and support manufacturing are becoming increasingly automated. In many respects, engineering automation is very similar to factory automation; both phenomena can dramatically improve labor productivity and both increase the proportion of knowledge work for the remaining employees. However, for many companies, the economic payback structure and the justification procedures for the two technologies can be quite different. This difference between engineering automation and factory automation stems from a difference in the scale economies of the two types of technologies. In many settings, the minimum efficient scale for engineering automation is quite low. Investment in an engineering workstation can often be justified whether or not it is networked and integrated into the larger system. The firstorder improvement of the engineer's productivity is sufficient. For justification of factory automation, the reverse is more frequently the case. The term "island of automation" has come to connote a small investment in factory automation that, by itself, provides a poor return on investment. Many firms believe that factory automation investments must be well integrated and widespread in the operation before the strategic benefits of quality, lead time, and flexibility manifest themselves. Computer-aided design is sometimes used as an umbrella term for computer-aided drafting, computer-aided engineering analysis, and computer-aided process planning. These technologies can be used to automate significant amounts of the drudgery out of engineering design work, so that engineers can concentrate more of their time and energy on being creative and evaluating a wider range of possible design ideas. For the near future machines will not typically design products. The design function remains almost completely within the human domain. Computer-aided engineering allows the user to apply necessary engineering analysis, such as finite element analysis, to propose designs while they are in the drawing board stage. This capability can reduce dramatically the need for time-consuming prototype work up and test during the product development period. Computer-aided process planning helps to automate the manufacturing engineer's work of developing process plans for a product, once the product has been designed. Planning and Control Automation Planning and control automation is most closely associated with material requirements planning (MRP). Classical MRP develops production plans and schedules by using product bills of materials and production lead times to explode customer orders and demand forecasts netted against current and projected inventory levels. MRP II systems (second-generation MRP) are manufacturing resource planning systems that build on the basic MRP logic, but also include modules for shop floor control, resource requirements planning, inventory analysis, forecasting, purchasing, order processing, cost accounting, and capacity planning in various levels of detail. The economic considerations for investment in planning and control automation are more similar to that for investment in factory automation than that for engineering automation. The returns from an investment in an MRP II system can only be estimated by analyzing the entire manufacturing operation, as is also the case for factory automation. The integration function of the technology provides a significant portion of the benefits. INTEGRATION IN MANUFACTURING Four important movements in the manufacturing arena are pushing the implementation of greater integration in manufacturing: * Just-in-Time manufacturing (JIT), * Design for Manufacturability (DFM), * Quality Function Deployment (QFD), * Computer-integrated Manufacturing (CIM). Of these, CIM is the only one directly related to new computer technology. JIT, QFD, and DFM, which are organization management approaches, are not inherently computer-oriented and do not rely on any new technological developments. We will look at them briefly here because they are important to the changes that many manufacturing organizations are undertaking and because their integration objectives are very consonant with those of CIM. Just-in-Time Manufacturing (JIT) JIT embodies the idea of pursuing streamlined or continuous-flow production for the manufacture of discrete goods. Central to the philosophy is the idea of reducing manufacturing setup times, variability, inventory buffers, and lead times in the entire production system, from vendors through to customers, in order to achieve high product quality (conformity), fast and reliable delivery performance, and low costs. The reduction of time and inventory buffers between work stations in a factory, and between a vendor and its customers, creates a more integrated production system. People at each work center develop a better awareness of the needs and problems of their predecessors and successors. This awareness, coupled with a cooperative work culture, can help significantly with quality improvement and variability reduction. Investment in technology, that is, machines and computers, is not required for the implementation of JIT. Rather, JIT is a management technology that relies primarily on persistence in pursuing continuous incremental improvement in manufacturing operations. JIT accomplishes some of the same integration objectives achieved by CIM, without significant capital investment. Just as it is difficult to quantify the costs and benefits of investments in (hard) factory automation, it is also difficult to quantify costs and benefits of a "soft" technology such as JIT. A few recent models have attempted to do such a quantification, but that body of work has not been widely applied. Design for Manufacturability (DFM) This approach is sometimes called concurrent design or simultaneous engineering. DFM is a set of concepts related to pursuing closer communication and cooperation among design engineers, process engineers, and manufacturing personnel. In many engineering organizations, traditional product development practice was to have product designers finish their work before process designers could even start theirs. Products developed in such a fashion would inevitably require significant engineering changes as the manufacturing engineers struggled to find a way to produce the product in volume at low cost with high uniformity. Ouality Function Deployment (OFD) Closely related to Design for Manufacturability is the concept of Quality Function Deployment (QFD) which requires increased communication among product designers, marketing personnel, and the ultimate product users. In many organizations, once an initial product concept was developed, long periods would pass without significant interaction between marketing personnel and the engineering designers. As a result, as the designers confronted a myriad of technical decisions and tradeoffs, they would make choices with little marketing or customer input. Such practices often led to long delays in product introduction because redesign work was necessary once the marketing people finally got to see the prototypes. QFD formalizes interaction between marketing and engineering groups throughout the product development cycle, assuring that design decisions are made with full knowledge of all technical and market tradeoff considerations. Taken together, Design for Manufacturability and Quality Function Deployment promote integration among engineering, marketing, and manufacturing to reduce the total product development cycle and to improve the quality of the product design, as perceived by both the manufacturing organization and the customers who will buy the product. Like Just-in-Time, Design for Manufacturability and Quality Function Deployment are not primarily technological in nature. However, technologies such as Computer-aided Design can often be utilized as tools for fostering engineering/manufacturing/marketing integration. In a sense, such usage can be considered as the application of computer integrated manufacturing to implement these policy choices. Computer-interated Manufacturing (CIM) Computer-integrated manufacturing refers to the use of computer technology to link together all functions related to the manufacture of a product. CIM is therefore both an information system and a manufacturing control system. Because its intent is so all-encompassing, even describing CIM in a meaningful way can be difficult. We describe briefly one relatively simple conceptual model that covers the principal information needs and flows in a manufacturing firm. The model consists of two types of system components: * departments that supply and/or use information, and * processes that transform, combine, or manipulate information in some manner. The nine departments in the model are: 1. production 2. purchasing 3. sales/marketing 4. industrial and manufacturing engineering 5. product design engineering 6. materials management and production planning 7. controller/finance/accounting 8. plant and corporate management 9. quality assurance. The nine processes that transform, combine, or manipulate information in some manner are: 1. cost analysis 2. inventory analysis 3. product line analysis 4. quality analysis 5. workforce analysis 6. master scheduling 7. material requirements planning (MRP) 8. plant and equipment investment 9. process design and layout. To complete the specification of the model for a specific manufacturing system, one must catalog the information flows among the departments and information processes listed above. Such an information flow map can serve as a conceptual blueprint for CIM design, and can aid in visualizing the scope and function of a CIM information system. Design and implementation of a computer system to link together all of these information suppliers, processors, and users is typically a long, difficult, and expensive task. Such a system must serve the needs of a diverse group of users, and must typically bridge a variety of different software and hardware subsystems. The economic benefits from such a system come from faster and more reliable communication among employees within the organization and the resulting improvements in product quality and lead times. Since many of the benefits a CIM system are either intangible or very difficult to quantify, the decision to pursue a CIM program must be based on a long term, strategic commitment to improve manufacturing capabilities. Traditional return-on-investment evaluation procedures that characterize the decision-making processes of many U.S. manufacturing concerns will not justify the tremendous amount of capital and time required to aggressively pursue CIM. Despite the high cost and uncertainty associated with CIM implementation, most large U.S. manu