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EN
The customer market is becoming more and more demanding. Customers want to have influence on the final shape, form, functionality and characteristics of the product. As a result, entrepreneurs are forced to abandon the Make-to-Stock system in favour of the MTO (Make-to-Order) concept, with the purpose of not only meeting the customers’ needs, but also, for example, reducing the costs by manufacturing exactly the number of products which is currently demanded on the market. The article describes an example of a production task performed in the cellular structure. The customer required a substantial and abrupt increase (by 65%) of the production task. In order to tackle the problem, logistics engineering and lean manufacturing methods were applied. Having regard to the Industry 4.0 perspective, a concept of automated work cells was presented in order to minimise the role of the operator.
EN
This article intends to justify the gap in the research of similarity coefficient driven approaches and cell formation problems (CFP) based on ratio data in cellular manufacturing systems (CMS). The actual implication of ratio data was vaguely addressed in past literature, which has been corrected recently. This research considered that newly projected CFP based on ration data. This study further revealed the lack of interest of researchers in investigation for an appropriate and improved similarity coefficient primarily for CFP based on ratio data. For that matter a novel similarity coefficient named as Generalized Utilization-based Similarity Coefficient (GUSC) is introduced, which scientifically handles ratio data. Thereafter a two-stage cell formation technique is adopted. First, the proposed GUSC based method is employed to obtained efficient machine cells. Second, a novel part allocating heuristic is proposed to obtain effective part families. This proposed approach is successfully verified on the test problems and compared with algorithms based on another similarity coefficient and a recent metaheuristic. The proposed method is shown to obtain 66.67% improved solutions.
EN
This paper presents the concept and methodology for the designing of a “tree-shaped” production line. The concept is a result of the search for production unit organization that meets the Lean Production assumptions, i.e. focusing on lead time (throughput time) shortening with simultaneous ability of use in conditions of varied product range. The varied product range characterized by lower technological-organizational similarity when compared to “Ushaped” units typical for Lean Production. The paper presents an algorithm for the designing of a “tree-shaped” production line and examples of its application. The designed unit underwent evaluation according to the criteria preferred by Lean Manufacturing experts. The designed production unit achieved results confirming the effectiveness of the proposed concept for the analysed sets of input data on the product range and production capacities.
PL
Podejście systemowe pozwala zobaczyć przedsiębiorstwo produkcyjne jako złożony system urządzeń służących do wytwarzania i urządzeń pomocniczych. W podejściu procesowym to produkcja sprawia, że strumień materiałów przepływa przez poszczególne komórki o mieszanej strukturze w sposób dyskretny (w krokach). Czas przetwarzania jest inny na każdym etapie wytwarzania. Elementem łączącym poszczególne urządzenia produkcyjne są bufory (składowiska) międzyoperacyjne, które pełnią funkcje przechowywania półwyrobów wytwarzanych w obiekcie N i magazynu dostaw do następnej komórki (N + 1) lub do innego obiektu. Parametry etapów zależą od czasu obróbki i wielkości partii. Analizowany proces wytwarzania urządzenia chłodniczego ma strukturę gniazdową. Istotnym elementem produkcji jest odpowiednie planowanie wytwarzania potrzebnych komponentów i montażu, by czas wykonania zadania produkcyjnego był jak najkrótszy.
EN
A systemic approach allows to see the production enterprise as a complex system of production and auxiliary facilities. In the process approach, it is manufacturing that makes the stream of materials flow through individual production cells in a mixed (serial – parallel) system, in a discreet way (in steps). Processing times are different at each stage. The element that connects the individual production facilities is buffer storage, which functions as a storage site for semi-finished goods departing from facility N or a delivery warehouse for the next site (N + 1) or to another station. The steps’ parameters depend on the processing time and batch size. The analyzed plant consists of 9 stations and buffers (warehouses). The process of manufacturing the refrigerating appliance has a cellular layout. An important part of production is the proper scheduling of production of the necessary components and assembly, so that the time of realization of the production task is as low as possible.
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EN
In the intensive competitive environment of the global economy, the survival of even the most well-established the world manufacturers depends on the ability to improve continuously quality while reducing costs. The resulting higher productivity is the key to market leadership and gaining sustainable competitive advantage. This paper outlines a group technology and classification of products which improve productivity, quality, inventory management of a company and reduce production times.
6
Content available remote A hybrid heuristic based clustering algorithm to design manufacturing cell
51%
EN
The manufacturing cell formation problem consists of designing a subclass of machine cells and their corresponding part families with an objective to minimize the inter-cell and intracell moves of the items while enhancing the machine utilization. This paper demonstrates a hybrid heuristic algorithm namely HACCF (Heuristic based Agglomerative Clustering for Cell Formation) exploiting the centroid linkage clustering method and the Minkowski distance metric as dissimilarity coeffcient. An exhaustive heuristic technique is developed and combined with the proposed clustering method to form manufacturing cells. 15 widely practiced datasets are obtained from past literature and tested with the proposed technique. The computational results are exhibited using the grouping efficacy as performance measure for the abovementioned test problems. The proposed technique is shown to outperform the standard and published techniques such as ZODIAC, GRAFICS, TSP based genetic algorithm and simple genetic algorithm and attained 73.33% improved result by exceeding the solution quality on the test problems. Therefore the proposed technique could be extensively used and could be hybridized with intelligent approaches to obtain more improved result in the vicinity of future cellular manufacturing system.
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