998 resultados para Machine shops


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Työssä on pyritty löytämään ratkaisuvaihtoehtoja pesulaitteen horisontaalisen harjan nostomekanismin parantamiseksi. Nostomekanismia pyrittiin kehittämään vähemmän huoltoa vaativaksi, toimintavarmemmaksi sekä kustannuksiltaan halvemmaksi. Uusia vaihtoehtoja mekanismille pyrittiin löytämään järjestelmällisen ideoinnin avulla, käyttäen hyödyksi alan kirjallisuutta, käytössä olevia pesulaitteita sekä jokapäiväisessä elämässä eteen tulleita havaintoja. Korroosiota aiheuttavat olosuhteet, horisontaalisen harjakokoonpanon pitkä liikerata sekä paino asettavat erityisvaatimuksia uudelle mekanismille. Lisäksi mekanismin täytyy liikuttaa harjaa vertikaalisessa suunnassa vakiona pysyvällä nopeudella. Valittuja ratkaisuvaihtoehtoja tarkasteltiin pistearvioinnin avulla ennen jatkokehittelyn aloittamista. Alustavassa komponenttien mitoituksessa pyrittiin mekanismin komponenteille löytämään oikea valmistusmateriaali sekä komponenttien geometriset mitat. Mekanismin valmistuskustannuksia eri valmistusmenetelmien kesken kartoitettiin yhteydenotoilla eri konepajojen kanssa. Alustavien kustannuslaskelmien perusteella jatkokehittelyyn otetun mekanismin kustannukset on 70 prosenttia pienemmät kuin nykyisen mekanismin kustannukset. Osien vähyys sekä mekanismin yksinkertaisuus lisää nostomekanismin luotettavuutta sekä vähentää tarvittavia huoltotoimenpiteitä.

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El GREP (grup de recerca de producte, procés i producció) de la UdG actualment disposa d’una eina informàtica desenvolupada en un PFC del 2003 que li permet fer la seqüenciació de la producció d’un taller mecànic amb un màxim de cinc productes, un nombre definit de possibles rutes de fabricació per a cada producte i tres màquines. Aquesta eina és molt resolutiva per a aquests casos, ja que estudia totes les possibilitats i les comprova una per una. No obstant aquest fet presenta una sèrie de limitacions com són el temps d’execució doncs al comprovar totes les seqüències té un elevat cost computacional i la rigidesa del sistema doncs no ens permet seqüenciar més productes ni més màquines. Per tal de donar solució a aquest problema es planteja generar una nova eina informàtica a partir de l’actual però que permeti seqüenciar més peces sense ocupar tanta memòria per així implementar-hi futures millores com el temps de preparació etc... Per a desenvolupar l’eina informàtica s’han utilitzat mètodes heurístics, concretament dos que són: algoritmes genètics i cerca TABU. Aquests mètodes destaquen perquè no busquen totes les combinacions possibles sinó que estudien una sèrie de combinacions i utilitzant mètodes de creuament i generació d’entorns busquen una solució

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In this paper, we study a problem of scheduling and batching on two machines in a flow-shop and open-shop environment. Each machine processes operations in batches, and the processing time of a batch is the sum of the processing times of the operations in that batch. A setup time, which depends only on the machine, is required before a batch is processed on a machine, and all jobs in a batch remain at the machine until the entire batch is processed. The aim is to make batching and sequencing decisions, which specify a partition of the jobs into batches on each machine, and a processing order of the batches on each machine, respectively, so that the makespan is minimized. The flow-shop problem is shown to be strongly NP-hard. We demonstrate that there is an optimal solution with the same batches on the two machines; we refer to these as consistent batches. A heuristic is developed that selects the best schedule among several with one, two, or three consistent batches, and is shown to have a worst-case performance ratio of 4/3. For the open-shop, we show that the problem is NP-hard in the ordinary sense. By proving the existence of an optimal solution with one, two or three consistent batches, a close relationship is established with the problem of scheduling two or three identical parallel machines to minimize the makespan. This allows a pseudo-polynomial algorithm to be derived, and various heuristic methods to be suggested.

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Historically downtime data collection and reporting systems in many automotive body panel press shops has been somewhat adhoc. The impetus for this study stems from frustration in respect of how this data is collected, assessed for trends and presented. Ideally this data should be used to identify costly repetitious faults for actioning of maintenance work and for feedback to tool design for consideration when designing new parts.

Presently this data is stored largely in the form of tacit knowledge by press shop operators; the encumbrance of transferring such information being that there is very often only limited channels to quantify it into something more tangible. Findings show that there tend to be two related obstacles to plant data recording. The first is that automation of down time data collection alone cannot determine fault causes as the majority of press shop events are initiated primarily from operator observation. The second is that excessive subjective operator input can often result in confusion and end up taking greater time in recording than remedying the actual fault.

This Paper presents the development of a system that through press mounted touchscreens encourages basic subjective operator input and relates this with basic objective data such as timekeeping. In this way all responses for a given press line become valuable and can be trended and placed in a hierarchy based on their percentage contribution to downtime or statistical importance. This then is capable of statistically alerting maintenance, line flow and/or toolbuild areas as to what issues require their most urgent attention.

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The integrated production scheduling and lot-sizing problem in a flow shop environment consists of establishing production lot sizes and allocating machines to process them within a planning horizon in a production line with machines arranged in series. The problem considers that demands must be met without backlogging, the capacity of the machines must be respected, and machine setups are sequence-dependent and preserved between periods of the planning horizon. The objective is to determine a production schedule to minimise the setup, production and inventory costs. A mathematical model from the literature is presented, as well as procedures for obtaining feasible solutions. However, some of the procedures have difficulty in obtaining feasible solutions for large-sized problem instances. In addition, we address the problem using different versions of the Asynchronous Team (A-Team) approach. The procedures were compared with literature heuristics based on Mixed Integer Programming. The proposed A-Team procedures outperformed the literature heuristics, especially for large instances. The developed methodologies and the results obtained are presented.