Complexity Of Assembly Systems Research Articles

Assessment of Product Variety Complexity

Product variety complexity assessment plays a vital role in system design, as it has tremendous negative effects on manufacturing complexity in assembly systems and supply chains. On the other hand, practitioners and researchers frequently consider the number of product variants as a sufficient measure to be used to manage this kind of complexity. However, as shown in this study, such a measure does not reflect all pertinent features of complexity. Therefore, the main goal of the paper is to develop a measurement method for product variety complexity that adequately reflects relevant relations between the portfolio of optional components and the number of product variants. As presented in the paper, the concept of information theory can be effectively applied to measure product variety complexity. Moreover, such a measure can also be useful to better understand this system's properties in order to reduce the level of variety-induced complexity. As such, the proposed method can be viewed as a complementary tool for reducing manufacturing complexity in terms of mass customization. The developed complexity metric was successfully tested on a realistic design example.

Product Interface Design for Complexity Management in Assembly Systems

Manufacturing firms are facing the challenge of minimizing variety-induced complexity in assembly systems. One of the effective approaches to complexity management is to reconfigure the assembly system by rearranging its assembly sequence. In order to rearrange an assembly sequence, a design-oriented approach is necessary because assembly is an activity of connecting parts through an interface between them. It means that the assembly sequence in production is restricted by the structure of interface connections in design. In this vein, this paper introduces a new design-oriented approach called interface design approach to complexity management in assembly systems. First, the mechanism of how the structure of interface connections affects assembly system complexity is identified. Then, an interface design framework is proposed for effectively finding an optimal interface structure and its assembly sequence to minimize assembly system complexity. For evaluating the complexity, the operator choice complexity index is adopted and modified for the interface design problem. In the case study, the framework is applied to the interface design problem by using industrial data of a plasma display panel (PDP) family from LG Electronics. The result of the study demonstrates that the assembly system complexity is significantly reduced by the proposed interface design framework.

Modeling and application of configuration complexity scale: concept for customized production

In current business environment, many original equipment manufacturers (OEMs) are employing mass customization strategies, which have implication on the entire operations of an enterprise and especially influence the character of their assembly processes. Increased product differentiation in context of mass-customized production (MCP) causes significant changes in complexity of assembly systems. Our focus in this paper is on the development of a methodological framework of mass-customized assembly modeling all possible product configurations and variants based on the number and type of assembly components from which final product configurations are completed. Subsequently, we propose an approach to determining the so-called configuration complexity scale based on combinatory used for many years as a foundation of methodologies for assessments of variety. The underlying hypothesis in this study is that configuration complexity scale offers a generic complexity framework for decision-making on variable products and production structures within Industry 4.0 concepts. The presented methodological framework is further applied on a particular case model of mass-customized assembly.

Modeling and application of mixed model assembly system complexity introduced by auto-body personalization

Assembly system complexity, especially welding system complexity introduced by auto-body product personalization is regarded as a major contributor of uncertainty in the system planning and designing. The welding system complexity is defined based on information entropy theory, the station-level integrated complexity model, and system-level complexity flow model are established to obtain the complexity source of welding system. Complexity source sensitivity indices are proposed to indentify key station and key equipment that contribute most to the complexity. Based on the application of auto-body side welding line case, the result indicates that the proposed complexity model and key complexity source identifying and diagnosing process can be used as the decision support tool of auto-body welding system.

The Influence of Mass Customization Strategy on Configuration Complexity of Assembly Systems

In current business environment many OEM companies are employing mass customization strategy, which has implication on the entire operations of an enterprise and especially influences the character of assembly processes. Increased product differentiation in context of customized production causes significant changes in complexity of assembly systems. Our focus in this paper is the development of methodological framework for generating all possible product configurations based on number of stable and optional components or modules from which a final product is completed. Subsequently, we propose an approach to determining so called product configuration complexity by specifying classes and sub-classes of product configurations. Then, for each sub-class of product configuration we can obtain upper bounds values of configuration complexity. Finally, configuration complexity scale based on the obtain upper bounds values is outlined and discussed.

A Case Study Measuring the Impact of a Participatory Design Intervention on System Complexity and Cycle Time in an Assemble-to-Order System

The literature identifies that a better understanding of the relationship between people and complexity in assembly design and operation is needed. This need is studied here with an industrial case study and by employing a socio-technical approach: assembly system operators are invited to take an active role in the participatory design of an assemble-to-order system. To measure the impact of the design intervention, a before versus after comparison is made. The investigative process begins with 371 observation samples; elementary units of the cycle time population are tested with Welch's ANOVA and regression into complexity variables and a complexity ratio. The complexity ratio is correlated to cycle time with regression (R-sq>0.75, 95% confidence), highlighting improved complexity organization with the “after” working design strategy. The observation models are used to predict theoretical complexity ratios and cycle times for direct comparison with a paired t-test. In the case study, the participatory design intervention proves significant by decreasing mean cycle time by 0.72min/assembly. Based on these results, the investigative process proves useful in assessing assembly system complexity relative to a working design (complexity ratio) and mean cycle time.

Development of Metrics and a Complexity Scale for the Topology of Assembly Supply Chains

In this paper, we present a methodological framework for conceptual modeling of assembly supply chain (ASC) networks. Models of such ASC networks are divided into classes on the basis of the numbers of initial suppliers. We provide a brief overview of select literature on the topic of structural complexity in assembly systems. Subsequently, the so called Vertex degree index for measuring a structural complexity of ASC networks is applied. This measure, which is based on the Shannon entropy, is well suited for the given purpose. Finally, we outline a generic model of quantitative complexity scale for ASC Networks.

The Complexity in Assembly Manufacturing System

Information-theory has been used to research the manufacturing system complexity for decade years. In order to describe the complexity more accurately, the assembly manufacturing system is aimed in this paper. The hierarchy structure of the assembly manufacturing system is first analyzed. The assembly system complexity is classified as structure complexity, process complexity and control complexity. In order to improve the complexity model, the process complexity is furthermore classified as static and dynamic process complexity which can describe the complexity of ideal and actual production process respectively. Then an integrated complexity model is proposed based on the classification.

Virtual Commissioning of an Assembly Cell with Cooperating Robots

The Virtual Commissioning (VC) technology is the latest trend in automotive assembly which, among other benefits, promises a more efficient handling of the complexity in assembly systems, a great reduction in the system’s ramp-up time, and a resulting shortening of the product’s time to market. This paper presents the application of VC techniques to the case of an industrial robotic cell, involving cooperating robots. The complete workflow of the virtual validation of the cell is presented, and the implementation requirements are discussed. Based on the findings, the outlook and challenges for the wide-range adoption of VC technologies in large-scale assembly systems are provided.

Complexity mapping of the product and assembly system

PurposeThe purpose of this paper is to present methods for assessing and mapping the complexity of products and their assembly. In cases of complexity of assembly it is important to consider and model at the product design stages when only data about individual parts/products and their assembly attributes are known. Assessing the complexity of assembly systems, based on the attributes of their components, is an essential step towards designing them for the least complexity.Design/methodology/approachThis paper presents a mapping method between the complexity of products and their variants and complexity of the system needed to assemble them. A method has also been developed to assess and compare the complexity of assembly systems based on the characteristics of their physical components for comparison and re‐design to reduce complexity.FindingsThe complexity dependency matrix estimates the average assembly equipment complexity for a certain product based on the interactions between parts handling, insertion and assembly attributes and assembly system functions. An automobile engine piston, domestic appliance drive, car fan motor and a three‐pin electric power plug products were used to demonstrate the application of the developed methodology.Originality/valueThe developed methods can be used by products and assembly systems designers to identify and alleviate major sources of complexity.

A model for measuring complexity of automated and hybrid assembly systems

The demand for delivering product variety has been increasing. Increased product variety caused by product customization, personalization, evolution and changes in their manufacturing systems. Variety allows manufacturers to satisfy a wide range of customer requirements, but it can also be a major contributing factor to increased complexity of assembly. Complexity is generally believed to be one of the main causes of the present challenges in manufacturing systems such as lengthy and costly design processes, higher life cycle costs and the existence of numerous failure modes. Complex assembly systems are costly to implement, run, control and maintain. Assessing complexity of assembly helps guides designers in creating assembly-oriented product designs and following steps to reduce and manage sources of assembly complexity. On the other hand, reducing complexity of assembly helps lower assembly cost and time, improves productivity and quality and increases profitability and competitiveness. The complexity of assembly should be assessed by considering both products and their assembly systems. In this paper, a structural classification coding scheme has been used to measure assembly systems complexity. It considers the inherent structural complexity of typical assembly equipment. The derived assembly systems complexity accounts for the number, diversity and information content within each class of the assembly system modules. A domestic appliance drive assembly system is used to demonstrate the use of the classification code to calculate the assembly system complexity. The developed complexity metrics can be used by designers as decision support tools to compare and rationalize various automated assembly systems alternatives and select the design that meets the requirements while reducing potential assembly complexity and associated cost.

Manufacturing complexity in assembly systems with hybrid configurations and its impact on throughput

A measure of product variety induced manufacturing complexity has been proposed based on the choices of assembly activities that operators make in serial, manual mixed-model assembly lines. In this paper we extend the complexity measure to assembly systems with parallel and hybrid configurations. The complexity measure takes into consideration operator choices at each station and the assembly system configuration. In addition, we develop throughout analysis models for assembly systems by incorporating complexity based on the operator reaction time and fatigue effects. The complexity and throughput models are applied to comparing performance of assembly systems with different configurations.

Product variety and manufacturing complexity in assembly systems and supply chains

Mixed-model assembly systems and modular supply chains are enablers to high product variety. However, as variety gets very high, the assembly and supply processes can become very complex. In assembly systems, the complexity may cause human errors and in turn impacts system performance. The complexity also impacts supply chain configuration and inventory control policy. This paper proposes a unified measure and models of complexity to assist in designing systems with robust performances. Complexity is defined as an entropy function of product variety and models are developed to describe the complexity propagation in multi-stage assembly systems and multi-echelon supply chains. Applications of the models are presented for complexity mitigation.