Concurrent Optimization of Product Module Selection and Assembly Line Configuration: A Multi-Objective Approach

A mixed-model assembly line is a type of production line where different models of a product are assembled on. Mixed-model assembly lines can respond to unanticipated changes in product demands quickly without keeping so many inventories. Designing mixed-model assembly line involves solving the traditional problems of the assembly line design (consists of balancing problem, determining cycle time, and the number and sequence of stations) in addition of determining the sequence of products in assembly line. The main goal of this paper is presenting a method in order to determine the sequence of products in mixed-model assembly line by considering Just-in-Time systems. Moreover, supplying some required components from feeding lines is considered. A mathematical model is presented which is capable of specifying the sequence of products in the mixed-model assembly line by considering main criteria and keeping feeding lines balanced. Mathematical model can be used for solving small-size problems. Because the combinatorial nature of sequencing problems typically provides an intractable search space for problems of “real world” size, the search heuristics of simulated annealing and ant colony algorithms are presented and used to find solutions for several problem sets. Experimentations show that the simulated annealing approach outperforms the ant colony approach in objective function performance.

Mechanical Bus for Modular Product Design

PurposeWhile the beneficial impact of supply chain integration (SCI) and modular product design are generally acknowledged, few empirical studies have examined how an organization can achieve better performance through SCI with modular product design. The purpose of this paper is to examine the relationship between SCI and modular product design, as well as their impact on product performance.Design/methodology/approachBy surveying 251 manufacturers in Hong Kong, structural equation modelling is used to test the research constructs and the hypothesized model.FindingsThe results confirm that information sharing, product co‐development and organizational coordination are crucial organizational processes within SCI. Companies that have high levels of product modularity appear to be good at product co‐development and organizational coordination directly and at information sharing indirectly. Furthermore, companies that have high levels of product co‐development or product modularity appear to have better product performance.Research limitations/implicationsThis paper theoretically and empirically identifies three specific organizational processes within SCI (information sharing, product co‐development and organizational coordination), which affect modular product design and product performance. These more specific findings were previously absent from the literature. However, the study is limited to the cross‐sectional nature of a survey study, the operationalization of SCI and product modularity, and the nature of the product types.Originality/valueThis paper empirically examines the relationships between SCI and product modularity, which has seldom been attempted in previous research. It clearly identifies exactly which processes within SCI are directly and indirectly related to product modularity.

Due to their many advantages, modular structures commonly exist in artificial and natural systems, and the concept of modular product design has recently received extensive attention from the engineering research community. Although some work has been done on modularity, most of it is qualitative and exploratory in nature, and little is quantitative. One reason for this gap is the lack of a clear definition of modularity. This thesis begins with a detailed discussion on the concepts of “modularity” and “module.” Based on the background presented here, a mutual information-based method is proposed to quantify modularity. The method is based on the view that coupling is information flow instead of real physical interactions. Information flow can be quantified by mutual information, which is based on randomness (or uncertainty). Since most engineering products can be modeled as stochastic systems and therefore have randomness, the mutual information-based method can be applied in very general cases, and it is shown that the commonly existing linkage counting modularity measure is a special case of the mutual information-based modularity measure. The mutual information-based method is applicable to final design products. But at the early stage of the engineering design process, there are generally only function diagrams. To exploit the benefits of modularity as early as possible, a minimal description length principle-based modularity measure is proposed to determine the modularity of graph structures, which can represent function diagrams. The method is used as criteria to hierarchically decompose abstract graph structures and the real function structure of an HP printer by evolutionary computation. Due to the specialty of genome representations in evolutionary computation, new genetic operators are developed to determine optimal hierarchical decompositions. This quantitative modularity measure has been developed to synthesize modular engineering products, especially by evolutionary design. There are many factors affecting evolving modular structures, such as genome representation, fitness function, learning, and task structure. The thesis preliminarily studies the effects of the modularity of tasks on the modularity of products in evolutionary computation. Using feed-forward neural networks as examples, the results show that the effects are task-dependent and rely on the amount of resources available for the tasks.

A Simulation Study on the Layout Design of Micro Assembly Line for Lens Module

The development of modular products is diffused in modern production due to the achievable flexibility and customization. Modular products can maximize the efficiency of manufacturing processes if they are structured to be easily configurable during the main assembly phases. In this context the present work proposes an approach to define the product modular architecture aimed to improve assemblability. The goal of this method is to achieve the product assembly sequence from the conceptual design phase. In particular it optimizes the conceptual design for assembly approach by taking into account the role of different flows in the modular product structure and the types of interface between modules. A case study allows the approach results to be shown and highlights the advantages and the drawbacks. An important improvement in the reduction of assembly time is shown in the context of household appliance manufacturing.

Product modularity and assembly systems: An automotive case study

Transitions towards a circular economy (CE) are based on the complementary development of novel circular business models and innovative product designs. Among the most prominent design strategies are modular product architectures that break products down into components that can be independently and easily replaced or reused. So far, most research has focused on technological and business model requirements for modular products but neglected the role of consumers. With the example of smartphones, the chapter shows how the co-shaping of technological and consumer trends does not provide an easy starting point for the modularity of smartphones in a CE. It investigates modularity as a sociotechnical arrangement embedded into people’s everyday lives and reveals that different forms of modular designs and accompanying services need to be implemented to move towards a more sustainable use of smartphones. The chapter concludes that an efficient and sufficient use of modularity as a part of transitions towards a CE cannot be enabled by modular product designs and services alone but would need more political regulation and standardisation.

Modular product design, as part of a product family strategy, is a key methodology for mass customisation and significantly impacts production line configuration. Common modules shared across product families, generations, and the entire product platform have varying lifecycles due to constant changes in market demand. Therefore, it is crucial to design a production line that can quickly respond to product change requirements while maintaining flexibility in both product and process variants. The objective of this research is to develop a hybrid decision-making framework for determining an optimal production line configuration based on product modularity and lifecycle. In the proposed framework, three scenarios related to production line configuration are modelled as batch, mixed-model, and intermittent production lines based on specific product lifecycle. After modelling the three lines, data on processing times and inventory levels are gathered, while assumptions for additional data are made with industry collaborators. The proposed models are used as evaluation criteria in a Multi-Criteria Decision-Making (MCDM) framework to determine an optimal production line configuration by integrating product modules and lifecycle. The proposed research demonstrates the performance of the three scenarios quantitatively with eight sub-performance indicators, utilising a hybrid MCDM and real production line simulation data.

In this chapter, a system to support the design of assembly and production lines used in the make-to-order production phase is presented. The relevance of the system is supported by the fact that current market dynamics often leads to frequent modifications in the allocation of manufacturing resources, and, as a result, decisions related to manufacturing systems design that used to belong to the strategic level are now taken at the tactical level, and thus require new tools to support them.The decision support system addresses two different categories of problems: (i) assembly line balancing and (ii) production line balancing. Due to the high complexity of these problems, it uses heuristic methods based on evolutionary computation approaches to tackle them. The system aggregates several modules to address the different problems, a database to handle both input and output data and an interface that enables a user-friendly interaction with the decision maker.

On the selection of a printed circuit board assembly line system

Gökçen et al. (2006) have proposed several procedures and a mathematical model on single-model (product) assembly line balancing (ALB) problem with parallel lines. In parallel ALB problem, the goal is to balance more than one assembly line together. In this paper, a network model for parallel ALB problem has been proposed and illustrated on a numerical example. This model is a new approach for parallel ALB and it provides a different point of view for interested researchers.

Aiming at the problem of product family assembly line (PFAL) evolution balancing, an evolution balancing model for PFAL is established and an improved algorithm based on NSGA_II is also proposed. Firstly, the product family evolution and assembly line characteristics are researched and analyzed in big data environment. Tasks on PFAL are divided into platform and personality tasks, and the stability of assembly tasks is mainly considered especially. In the optimization process, a chromosome encoding based on TOP sorting algorithm is adopted, and a new density selection and decoding algorithm is proposed to make up for the deficiencies in traditional algorithms. Finally, an example of PFAL planning is given to verify the effectiveness and feasibility of the improved NSGA_II.

The effective operation of individual pieces of production equipment, assembly lines, or whole factories is dependent on three dimensions of performance: The amount of time that it is available to run (availability) 2. The speed of the equipment (performance rate) 3. The quality of the product that it produces (quality rate). Equipment that is operating effectively scores highly on each of the above dimensions. If these metrics are viewed in isolation, they provide a valuable insight into the performance of the equipment, but the compound effect of all three of the dimensions provides surprising results. The compound effect is called the overall equipment effectiveness (OEE) and is obtained by simply multiplying the availability by the performance rate and the quality rate. This paper discusses the evolution of OEE and its future direction.

This study develops a new method called Overall Processes Capability Index (OPCI) to measure the capability of assembly lines. After defining relation between percentage yield and process capability, the new definition of overall defective rate is developed for assembly lines in different cases (series and parallel processes). The interesting point is that a rejected item from one process can be assembled with one another rejected item of another process and creates one accepted assembled one. Then regarding to this point and with the aid of transforming new definition of overall defective rate to process yield, the overall processes capability of assembly production line is measured.