Slavomir Bednar

The Impact of Customized Variety on Configuration Complexity of Assembly Process

Mass customization provides products with high variety on demand, at a cost not significantly greater than mass production. Problem at this point is that these product variants lead to process/resource variants what has a negative impact on complexity of manufacturing complexity of such products. In this paper, we present a methodological framework for creating all possible product variants based on unlimited number of optional components while assuming with at least two constant initial components. Development of all possible product architectures is further applied for investigation the impact of product variety decisions on structural complexity of assembly processes. According to the assembly process variants created a specific complexity measure can then be assigned.

Decision-Making Approach to Selecting Optimal Platform of Service Variants

Nowadays, it is anticipated that service sector companies will be inspired to follow mass customization trends of industrial sector. However, services are more abstract than products and therefore concepts for mass customization in manufacturing domain cannot be transformed without a methodical change. This paper is focused on the development of a methodological framework to support decisions in a selection of optimal platform of service variants when compatibility problems between service options occurred. The approach is based on mutual relations between waste and constrained design space entropy. For this purpose, software for quantification of constrained and waste design space is developed. Practicability of the methodology is presented on a realistic case.

Recognition of Assembly Parts by Convolutional Neural Networks

The paper describes the experiments with the use of deep neural networks (CNN) for robust identification of assembly parts (screws, nuts) and assembly features (holes), to speed up any assembly process with augmented reality application. The simple image processing tasks with static camera and recognized parts can be handled by standard image processing algorithms (threshold, Hough line/circle detection and contour detection), but the augmented reality devices require dynamic recognition of features detected in various distances and angles. The problem can be solved by deep learning CNN which is robust to orientation, scale and in cases when element is not fully visible. We tested two pretrained CNN models Mobilenet V1 and SSD Fast RCNN Inception V2 SSD extension have been tested to detect exact position. The results obtained were very promising in comparison to standard image processing techniques.

Resolving Product Configuration Conflicts

The main objective of this paper is to propose an approach to resolve product configuration conflicts based on the previously developed framework for product component modelling in terms of mass customization and original matrix method, by which it is possible to determine the number and structural designs of all relevant product configurations.

Assessment of Assembly Process Complexity and Modularity in Mass Customized Manufacturing

Consumers’ market is made up of huge number of products as a direct response to the ever increasing demands of customers. This situation is closely related to constantly evolving technical and technological industries. The rapidly increasing demand on products and variety of functional properties enabled a series of fast-growing and emerging processes and operations all over the industry. Unfortunately for companies, such variety results with a complexity of both, products and related processes. This paper deals with the external-product and internal-process complexity in the view of its usability within a mass customized manufacturing. A novel method to identify and measure product and process complexity of an assembly station is proposed on the basis of the number of product and process variants. Subsequently, the aggregated complexity ratios can provide a complexity map of an entire production line. The novel complexity assessment method is applied and verified on the case automotive manufacturing plant. As a result of this application, the newly-proposed complexity assessment methodology is highly useful especially in customized automotive production as an effective tool for assessing the level of complexity of a selected department, or when introducing a new installation. The newly-proposed methodology can be also adopted by a company to decide on what part or sub-module can be produced by external supplied—transfer of complexity—in order to decrease own process complexity and to keep the extent of variety offered to customers. Finally, based on the case application and verifications, the complexity assessment methodology proposed in this paper is highly applicable in the mass customized manufacturing.

Complexity Mitigation in Collaborative Manufacturing Chains

Collaborative manufacturing chains (CMSs) are understood as networks of manufacturing units that are highly specialized, cooperation-independent and economically autonomous. CMSs are becoming ever more complex in today’s global market and one pertinent task for supply chain designers/managers is to handle outsourcing decision-making problems, by which such complexity can be reduced. In this paper, we propose to solve this problem through generation of alternative collaborative manufacturing chains that are benchmarked using topological complexity metrics. For this purpose, firstly supply chain structures are modelled. Subsequently, topological complexity measures for each possible configuration network are quantified. Finally, optimal supply chain configurations are selected.

Supply Chain Complexity Measures Using Information Theory

One of the complexity metrics that contribute towards determination of the overall complexity of supply chains is based on so called static complexity. In this article, we firstly present an architectural framework for supply chain networks. Subsequently, selected complexity indicators based on Axiomatic Design theory and Boltzmann entropy are applied. The indicators used are benchmarked based on computational experiments. Finally, relevant conclusions are formulated.

Product Configurations in Terms of Mass Customized Assembly Systems

In current production and business environment many Original Equipment Manufacturers (OEMs) apply strategy of mass customization (MC). They do so in order to draw the attention of potential customers, by offering a high level of product customization. The product differentiation in context of mass-customized production (MCP) brings massive changes into facility operations, fundamentally influences the character and substance of assembly processes which causes significant changes in assembly complexity. This paper firstly presents a methodological framework for generation of product configurations depending on the composition and number of initial assembly components, subsequently, a procedure for assessment of configuration complexity is proposed. The presented methodological framework is further applied on a specific model of customized assembly of washing machines where the configuration complexity is further compared with generally applicable Shannon`s (entropic) structural complexity.

Design Optimization of the Assembly Process Structure Based on Complexity Criterion

This paper focuses on configuration design optimization of the assembly supply chain network. It is intended to use this approach to select an optimal assembly process structure in early stages of manufacturing/assembly process design. For the purpose of optimization, structural complexity measures as optimality criteria are considered. In order to compare alternatives in terms of their complexity, a method for creating comparable process structures is outlined. Subsequently, relevant comparable process structures are assessed to determine their structural complexity.