ایجاد زمان مرحله به مرحله سیستم های تولید ترکیبی

This paper develops a comprehensive method for transforming pure functional manufacturing shops into hybrid production systems that comprise both cellular and functional areas. The facility redesign approach first derives the layout of the work centers within each cell and then places the cells within existing departments according to a time-phased implementation plan. The incremental cell implementation is dictated by budget constraints that limit the allowable investment in each fiscal period. The goal is to maximize the net benefit from cell implementation, expressed as the difference between the savings in material handling effort and the cost of machine rearrangement. An explicit enumeration scheme provides the optimal intra-cell layout. The problems of cell placement and implementation sequence are integrated in an integer programming formulation. The decomposition of the mathematical model motivates a space search approach, which generates an optimal solution. All algorithms are integrated and used to transform the functional shop of a large manufacturer into a hybrid production area. The results illustrate that substantial benefits can be realized even with a conservative multiperiod implementation plan.

A typical job shop is organized along functional departments, with like processes/machine tools grouped together (Francis et al., 1992). While this shop organization provides a flexible layout that is readily adaptable to changes in the work mix, it results in increased move and queue times, thus large manufacturing cycle times and production costs (Ham et al., 1985). To minimize the inter-departmental flow and the non-value-added material handling effort, cellular manufacturing systems have been proposed (King, 1980). These systems comprise groups of machines that process families of parts (in terms of part attributes or routings), and require the clustering of machines into semi-independent groups (cell formation)-see Fig. 1. A plethora of mathematical programming and heuristic approaches have been developed to solve the cell formation problem (Kusiak and Chow, 1988). The majority of these algorithms are based on part similarities and other group technology considerations (Wemmerlov and Hyder, 1986), or require material flow and machine capacity information (Harhalakis et al., 1990). Recently, genetic algorithms (Hicks, 2004) and fuzzy decision-making (Gungor and Arkan, 2000) have also been proposed for the cell formation problem, which continues to intruigue researchers and practioners. Furthermore, several studies have addressed the advantages of cellular systems with respect to production effectiveness (see, e.g., Al-Mubarak et al. (2003) and D’Angelo et al. (2000)). Given the logical aggregation of work centers into cells, the layout of the resources within each cell must be designed. The intra-cell design problem has received relatively smaller attention compared to cell formation, and has been typically treated as a quadratic assignment problem (QAP) (Heragu, 1992). The usual objective is the minimization of the cumulative product of the material flow and the distance between the cell's work centers. For a comprehensive survey of heuristics to solve the intra-cell design problem see Kusiak and Heragu (1987). In several industrial applications however, it has been observed that solving the general QAP for intra-cell layout results in unordered clusters of machines which do not facilitate the flow of parts through the cell (Lu, 1993). Thus, additional constraints or different objectives are necessary to drive the solution towards the three intra-cell layout types usually desired in modern manufacturing systems, i.e., linear single and double row and U shaped arrangements (see Heragu (1992) and Hassan (1995)). The final stage in the design of a cellular facility is the determination of the location of the cells on the shop floor. The problem has been treated as a QAP as well, with various objectives (Francis et al., 1992, Meller, 1994 and Gomez et al., 2003), usually targeting minimal inter-cell material handling. However, since most of the flow is confined within the cells, minimization of inter-cell material handling may not be the most appropriate objective, since the associated cost is minimal by design (cell formation) for pure cellular configurations (Liang and Taboun, 1995). Most design methods for cellular manufacturing systems developed to-date address a clean-slate problem, i.e., they assume that any change in the shop area is feasible or may be performed with negligible costs. Thus, they concentrate independently on the clustering or layout problems, and ignore significant implementation issues (Logendran, 1993). However, if we addresses the reconfiguration of an existing facility from a functional arrangement to a cellular system, several cost factors and inherent constraints have to be considered simultaneously. For example, newly formed cells may incur substantial machine relocation costs, or may comprise machines that cannot be placed in close proximity. Furthermore, the relocation of some machines may be infeasible due to their weight or permanent base. Also, redistribution of machines to departments must be complemented by several updates and reorganization of departmental ledger of accounts, which is usually undesirable since most manufacturers use specific departmental accounts to trace or allocate costs to individual products and resources (Ioannou and Sullivan, 1999). Finally, the formation of cells requires training and flexibility of the work force, with significant socio-technical impact (Harvey, 1994). Apart from inefficiencies related to implementation issues, a pure cellular configuration may not be practical due to the existence of bottleneck machines that cannot be assigned to cells. To overcome the above problems, hybrid manufacturing facilities comprising both manufacturing cells and groupings of like machine tools have been proposed to combine the benefits of cellular manufacturing with the flexibility of functional layouts (Ang and Willey, 1984). Hybrid configurations are preferable in the case that cells are formed within existing departments during shop reconfiguration. The main advantages of cell-within-department configurations are the minimal machine relocation costs and the negligible changes in departmental accounts. This paper presents a method for transforming job shops into hybrid facilities, with cells formed within existing departments, assuming that group technology or material flow-based cells have already been logically formed, and a subset of the most significant among them has been selected for implementation. The method consists of three steps: (i) Physical arrangement of the machines in each significant cell (intra-cell layout), (ii) layout of these cells and the remaining machines on the shop floor (cell-department layout), and (iii) development of a time-phased plan for realizing the cells with minimum rearrangement cost. Stages two and three are intertwined, due to their overlapping objectives which seek the best tradeoff between machine relocation costs and benefits from cell implementation. The implementation plan accounts for budget constraints in each time period. The problem shares some similarities with the dynamic plant layout problem, which addresses period-varying material flow resulting in different layout designs (Balakrishnan et al., 2003). The proposed method has been applied to redesign the production and assembly shop of a large manufacturer of communications equipment. The facility produces in excess of 10,000 make items, and comprises 130 workstations arranged currently in functional departments. The remainder of this paper is organized as follows: Section 2, provides a comprehensive overview of the production environment considered in this work and the cell evaluation procedures. Section 3 describes the various objectives for the intra-cell layout problem and the implicit enumeration scheme employed to obtain optimal solutions. Section 4 formulates the problem of cell implementation over a time horizon as an integer program, and decomposes the mathematical model into two independent sub-problems that address the spatial and time-related cell formation. Section 5 presents a composite space search approach to obtain optimal solutions. Section 6 illustrates the application of the facility redesign approach to the manufacturing and assembly shop of a large antenna manufacturer. The paper concludes in Section 7.

This paper addressed some important issues that arise during the reconfiguration of an existing manufacturing facility. The main assumption is that the existing design comprises departments of functionally similar machines, while the target design is a hybrid system, comprising functional departments as well as manufacturing cells formed within existing organizational units. The logical grouping of machines into cells was considered as an input to our method, which provided the intra-cell design as well as the final location of all machines in the shop after a multi-period implementation period. An explicit enumeration scheme was used to derive the optimal intra-cell design. The problem of incremental cell implementation was formulated as a complex integer programming problem. The model was decomposed into the spatial and time-related cell formation. A composite algorithm employed the solutions of the two sub-problems to construct an optimal solution to the global problem. The method was applied to the redesign of the production, assembly and packaging area of a large manufacturer of telecommunications equipment. For this application, eight cells were identified as candidates for implementation, based on expected traffic savings. Four of these cells were finally proposed for spatial formation. The intra-cell design provided double row configurations for all cells, while the implementation plan resulted in a sequence that would yield net total savings of more than $350,000 over a two period time horizon and almost $200,000 thereafter. Several new areas for further work can emanate from this research. First, the underlying mathematical properties of the complex integer programming formulations could be studied. Second, the application of the methodology to other types of production environments (e.g., transforming functional department into flow lines or just-in-time U-shaped cells) could be pursued. Third, the integration of the approach developed in this paper with other global methods for layout and material handling systems design could be explored. And finally, the implementation of the proposed algorithms and methods into standard software for facilities layout could be examined.