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The dividing line between the sensible and efficient use of assembly robots and that of dedicated automatic assembly machines requires detailed planning.

With the development of laser welding technology, welding techniques are increasingly used in automatic assembly machines. The main advantage of laser welding is due to the contactless welding, which largely obviates the need of equipment maintenance.

Cycle time fluctuations in assembly lines are one of the important reasons of re‐balancing. As a result of re‐balancing of assembly lines, it will be necessary to change task sequences or equipment locations. The purpose of this paper is to find the task sequence which enables assembly line balancing (ALB) with minimum number of stations (NS) for different cycle times such that tasks and equipment or fixture locations remain unchanged.

In this paper a heuristic which consist of two stages is proposed to find a common task sequence for different cycle times in assembly lines.

It is shown that optimal NS for different cycle times can be achieved with a fixed task sequence.

The approach is limited to a single model case. Model variety together with cycle time variety can be investigated in further studies.

Assembly lines which require less time and cost for re‐balancing can be easily designed by the proposed approach.

ALB problem is handled with a new viewpoint. Also, it is observed that the proposed approach serves as a bridge between assembly line design and balancing. In this regard, it is thought to have an important place in the ALB literature.

The purpose of this paper is to provide a methodological guidance for the practical use of the axiomatic designed production module template presented in a former publication. The objective is to accelerate the design process and increase the quality of results in the design of lean production systems.

Two case studies based on practical cases were presented to different test teams. A first test cycle helped to improve the user friendliness of the axiomatic designed tree of functional requirements and design parameters. The second test cycle served to prove the practicability of the template, comparing the teams' results with the realized solution.

Based on the teams' feedbacks, ten “easy‐to‐use” steps for the systematic design of lean production systems were developed. The guideline obtains the best results if used in combination with the value stream mapping concept.

Apart from one case study in injection moulding, practical evaluations were focused on applications in the field of manual, hybrid or automated assembly systems, which perhaps limits the applicability of the presented approach in some machining processes.

Several successful implementations demonstrated the validity of the presented method in terms of results, planning time and user friendliness. Even students with nearly no practical experiences in production system design were able to present astonishing results within short timeframes.

This paper fulfils an identified need of a methodological guidance in the design of lean production systems and offers practical help to shorten the design times and improve the quality of the design results.

The paper aims to discuss the importance of considering both the physical and cognitive automation when aiming for a flexible or reconfigurable assembly system. This is done in order to handle the increased demand for mass customized production and to maintain or improve the social sustainability within the company.

The methodologies used in this paper are a theoretical review about task allocation and levels of automation and a methodology called DYNAMO++ for the industrial case studies.

The paper provides both theoretical and empirical insights about the importance of considering both the cognitive and physical automation when aiming for a reconfigurable assembly system.

The paper will only discuss the cognitive strategy from a social sustainability perspective and not from an economical or environmental angle.

The paper presents data from three industrial case studies, mostly in the automotive industry. The result points towards a need for a more structured and quantitative method when choosing automation solutions, furthermore an increased use of cognitive automation solution.

The results from the case studies show that when the complexity and variety of products increases, a cognitive support for the operators is needed. This strengthens the theory of a need for a cognitive automation strategy within companies.

The paper demonstrates an advance in the state of the art in task allocation. The concept model and the DYNAMO++ method can be seen as a step closer towards quantitative measures of task allocation (i.e. changes in both physical and cognitive LoA) and dynamic changes over time.

The purpose of this paper is to develop and test a design approach based on the investigation of the sensitivity of assembly systems to volume fluctuations as part of the selection process of alternative design solutions for scalable assembly systems on the basis of a real industrial case study.

A conceptual approach for the (re‐)design of a scalable assembly system is developed on the basis of an industrial case research using axiomatic design (AD) for the top level structuring of the framework incorporating useful methods and insights obtained from a thorough literature review and from previous research work.

The findings of this research are limited due to the focused nature of a case study based research. However, the obtained results encourage assuming its transferability to similar problems.

Significant research has been done in the design of assembly systems for high product variety, but the review of literature in this field still identifies many opportunities for future research. This paper responds to the clearly identified research need of a methodological guidance regarding the design of scalable assembly systems and offers a practically proven help to improve the efficiency of the design process and the quality of the design results.

The purpose of this paper is to transfer the idea of changeability to a concrete technical application.

Based on the definition of changeability on a factory level, a transformation of the five change enablers specified therein for the work station level using the example of an aerodynamic feeding system takes place in this paper.

The observed aerodynamic feeding system can be determined as changeable.

Changeable systems are able to react with low effort to exterior influences, e.g. of the market, and thus represent a considerable competitive advantage.

The new element in this paper is the observation of change enablers on the work station level. This point of view enables the concrete figuration of changeable technical systems.

The increasing demand for market‐oriented production leads to shorter product life‐cycles, growing product variety and, therefore, changing lot sizes. These critical lot sizes vary greatly in number. Because of this, the question of whether or not to prioritize fully automated or manual assembly arises. The intention to meet the requirements of a turbulent market leads to hybrid assembly systems in which automated and manual assembly stations operate together flexibly. This hybrid system, supported by modular structures with defined interfaces and process software, allows a fast reaction to any change in products, variants and lot sizes. Owing to the difficulty in accessing materials, traditional assembly systems have a high contingent of non‐value adding procedures. By collecting materials in advance within one main area and distributing them to the work stations simultaneously for the production of a good, a minimized quantity of material is present on the assembly line, thus making the process more efficient.

This paper presents a versatile and economical knowledge‐based assembly design of blade and shell assemblies by employing behavioral modeling concepts. Behavioral modeling is a new generation CAD concept aimed at achieving ultimately optimum results with the efforts made in the early stage of the product development cycle. As a result, the assembly process of any odd‐configured parts such as torque converter blades, can be accurately planned, and made adaptable to all potential in‐process alterations due to either changes of components design or that of the assembly kinematics. Optimum assembly design is achieved when the volumetric interference meets a desired value based on an expert's determination. Experimental verification of the proposed optimum assembly design conducted in Luk, Inc. with two different blades' assemblies demonstrates satisfactory results.

The 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.

This 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.

The 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.

The developed methods can be used by products and assembly systems designers to identify and alleviate major sources of complexity.