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In the last two decades, many researchers have addressed the superior system performance resulted from the integration of process planning and scheduling functions. However, most of the published solution methods in this field fall short in three accounts. First, while integrating with scheduling, they ignore the checking of process planning feasibility with respect to tolerances allocation. Thus, operational tolerances may stackup beyond the blue print tolerances making the process plans infeasible. Second, they ignore the machines capabilities during the integration modeling which make these solution models practically inapplicable. Third, they focus on time consideration, such as makespan or lateness, and do not consider manufacturing cost related to operations-machines assignment. This paper presents an innovative model for the integration of process planning and scheduling in a job-shop environment. The model simultaneously serves three purposes: allocating operational tolerances while minimizing its manufacturing cost, minimizing the work in process inventory, and figuring the operation-machine assignments. The preemptive-goal programming method is used to solve the proposed multiobjective non-linear mixed integer model, and an implementation example is presented to demonstrate the effectiveness of the proposed modeling approach. [ABSTRACT FROM AUTHOR]

Tolerances play an important role in product fabrication and have a significant impact on manufacturing costs. The factors affecting manufacturing cost (geometry, material, etc.) of a part are fuzzy or subjective in nature since they have no appropriate numerical measure. This paper proposes a framework that overcomes the drawbacks of traditional tolerance control methods and reduces subjectivity via fuzzy comprehensive evaluation and conjoint analysis. In the fuzzy comprehensive evaluation process, the relationship between the machining costs and part tolerance is expressed through a mathematical formula, with the objective of minimizing the total machining cost. The conjoint analysis method is introduced to provide a systematic method of deciding weights for each of the factors in the tolerance allocation procedure. The application of the framework is demonstrated with practical engineering problems of allocating tolerances of an accumulator's O-ring seal and a clutch assembly. [ABSTRACT FROM AUTHOR]

Tolerance allocation is a design tool for reducing overall cost of manufacturing while meeting target levels for quality. An important consideration in product design is the assignment of design and manufacturing tolerances to individual component dimensions so that the product can be produced economically and functions properly. The allocation of tolerances among the components of a mechanical assembly can significantly affect the resulting manufacturing costs. In this work, the tolerance allocation problem is formulated as a non-linear integer model by considering both the manufacturing cost of each component by alternate processes and the quality loss of assemblies so as to minimise the manufacturing cost. Metaheuristics techniques such as genetic algorithm and particle swarm optimisation are used to solve the model and obtain the global optimal solution for tolerance design. An example for illustrating the optimisation model and the solution procedure is provided. Results are compared with conventional technique and the performances are analysed. [ABSTRACT FROM AUTHOR]

For aircraft structures, it is clear that the design and the selection of materials play an important role in the performance of the aircraft. The production costs are also important. The concept of tailor-made blanks (TMBs) is based on the use of dedicated blanks, made of different alloys and/or thickness in order to satisfy different demands such as an increase, if necessary, of local strength, stiffness, and damage tolerance. This paper describes the results of a study to assess the potential weight and cost savings of using TMBs in a typical aerospace structure. A bonded structure representing the floor beam of an aircraft has been selected, analyzed, and tested to validate the numerical and analytical predictions made with MATLAB and finite-element method. The results show weight reduction of 12% and 37% for two studied configurations, compared to the reference beam. [ABSTRACT FROM AUTHOR]

Robust design can significantly improve a producer’s competitive ability to deliver high-quality products with low development cycle time, quality loss, failure cost, and tolerance cost. However, during usage by a consumer, the functional performance of a product or some of its components may change as use time passes, leading to unexpected product failure that is usually costly in both time and money. The cost of these failures may influence the determination of optimal use time and optimal initial settings as compensation for the possible process mean changes during consumer usage. In addition to finding use time and initial settings for proper quality performance, the determination of process mean and tolerance also needs to be considered. As is known, changes in process means acquired quality loss and variability, while process tolerance has an effect on tolerance-related costs and quality loss. Because there exists a dependency among use time, initial setting of process mean, process mean, and process tolerance, these values must be determined simultaneously. Thus, in this paper, an optimization model with an acceptable reliability value is developed to minimize total cost, including quality loss, failure cost, and tolerance cost, by determining optimal use time, initial settings, process mean, and process tolerance, simultaneously. Applications of single and multiple components are presented to explain the proposed models. Finally, sensitivity analysis and model discussions on some decision variables are performed. [ABSTRACT FROM AUTHOR]

Tolerance transfer techniques are used extensively for allocation of tolerances for each machining operation in the process sequence, and hence are used to coordinate the process planning and the design activities in the evolution of a new product. This paper deals with an extended approach to allocate process tolerances based on a tree topology called technologically and topologically related surfaces (TTRS) and its subsequent extension to cost optimization. The benefit of this approach is that equations are generated explicitly with regard to tolerance transfer. These have been exploited by implementing the cost function in the generated explicit equations and subsequent optimization. The TTRS approach has been extended which scores over the limitations of some of the already existing techniques in that, it is optimal with respect to two factors namely, cost of producing the required tolerances, as also the process capability of the machines involved in producing the part. This technique has been proved practically feasible as it has been implemented in an industry. To enable a better view of the advantages of the approach, a comparative study with the existing techniques has been carried out in addition to a simulation using the Monte Carlo method. [ABSTRACT FROM AUTHOR]

Tolerance on parts dimension plays a vital role as the quality of the product depends on sub components tolerance. Thus, precision products that are manufactured reflect at high manufacturing cost. To overcome this situation, sub components of an assembly may be manufactured with wider tolerance, measured (using latest technologies like image processing) and grouped in partition and corresponding group components may be mated randomly. This present work is to obtain an optimum manufacturing tolerance to selective assembly technique using GA and to obtain maximum number of closer assembly specification products from wider tolerance sub components. A two components product (fan shaft assembly) is considered as an example problem, in which the subcomponents are manufactured with wide tolerance and partitioned into three to ten groups. A combination of best groups is obtained for the various assembly specifications with different manufacturing tolerances. The proposed method resulted nearly 965 assemblies produced out of one thousand parts with 15.86% of savings in manufacturing cost. [ABSTRACT FROM AUTHOR]