Åsa Fasth

Measuring and analysing Levels of Automation in an assembly system

The level of automation employed in semi-automated assembly systems is crucial, both to system performance and cost. This paper presents a methodology to enable selection of the right Level of Automation. The method thoroughly maps existing product and information flows as well as the automation level in separate parts of the system. It then analyses and identifies future automation possibilities, i.e. the automation potential seen from an industrial perspective. Further development of the method is based on validations and industrial case studies.

Enabling flexible manufacturing systems by using level of automation as design parameter

Handling flexibility in an ever changing manufacturing environment is one of the key challenges for a successful industry. By using tools for virtual manufacturing, industries can analyze and predict outcomes of changes before taking action to change the real manufacturing systems. This paper describes a simulation tool that can be used to study the effect of level of automation issues on the design of manufacturing systems, including their effect on the overall system performance, ergonomics, environment, and economic measures. Determining a suitable level of automation can provide a manufacturing system with the flexibility needed to respond to the unpredictable events that occur in factory systems such as machine failures, lack of quality, lack of materials, lack of resources, etc. In addition, this tool is designed to use emerging simulation standards, allowing it to provide a neutral interface for both upstream and downstream data sources.

Comparing quantifiable methods to measure complexity in assembly

In order to measure complexity and stay competitive, manufacturing companies need to be able to quantify production complexity. For this reason, two methods were developed within the context of two concurrent research projects are compared: the Belgian Complexity Calculator, CXC, measures objective complexity and the Swedish Complexity Index, CXI, focuses on subjective complexity, as experienced by operators in the stations. This paper presents a comparative analysis of the two methods by comparing them to seven relevant existing quantitative methods and by examining results from case studies. It is observed that the two methods can be used as a compliment to one another, where CXC can be used for scanning data automatically CXI can be used for in-depth analysis. In addition, the comparison of existing methods provides insight on how to measure complexity depending on need and scope.

Validation of the complexity index method at three manufacturing companies

In order to manage increasing numbers of product variants, tools that can reduce or manage production complexity are vital. The paper describes CompleXity Index (CXI), an index-based method and tool that assess the complexity at an industrial workstation. CXI was validated at three Swedish manufacturing companies investigating how different roles affect the index calculation and if the method measures what was intended. In all three cases, CXI was seen as a useful tool that provided a holistic view of the problems seen at a station. In addition it was indicated that complexity and unbalanced work was connected and that the method could be used to predict problem areas on new stations.

Characteristic of a Proactive Assembly System

Competitive assembly systems must cope with frequent demand changes, requiring drastically shortened resetting and ramp-up times. Characteristics of assembly systems capable of rapid change are e.g. Flexibility; Robustness, Agility, and ability to handle frequent changes and disturbances. This paper proposes proactivity as a vital factor of semi-automated assembly systems to increase speed of change. Proactive systems utilize the full potential of human operators and technical systems. Such systems have ability to dynamically change system automation levels, resulting in decrease of time consumed for assembly tasks. Proactivity criteria for assembly systems are reviewed based on theory and industrial case studies

A model for assessment of proactivity potential in technical resources

The ultimate aim when designing an assembly system is to make it strategically and operationally competitive. Competitive systems for manufacturing, especially assembly systems, have to cope with frequent changes of demands. The aim to have a short response time to customer demand, e.i. mass customization, requires assembly systems that are reliable, have high availability and have ability to produce the right product correctly. This means a combination of short resetting time and ability to vary the systems output of products. A major challenge is to minimize the lead-time that directly has influence on order-to-delivery time, while maintaining product flexibility and robustness to absorb late market changes. Given that the assembly system is working the way it is supposed to do, the order-to-delivery time is directly dependant on the setup time and the operation time. The problem is that automated assembly systems have a low availability due to that technical equipment does not work, caused by lack of knowledge, breakdowns, limited ability to perform the operation etc. This often leeds to that when a company needs variant flexibility they keep the assembly system tasks manual. Totally manual assembly system is not the future for competitiveness. Therefore we need to develop assembly systems that are available and have product flexibility to absorb late market changes, and still have a short order-to delivery time. This paper focuses on the level of automation and is a contribution to future evaluation of how technical solutions either support or work counter to proactivity. The result is a model for evaluation of technical solutions contribution to proactivity This paper describes a model for assessment of technology and assembly system solutions that fulfil requirements for a proactive assembly system. Criteria for proactivity in different technical solutions of assembly system are reviewed.

Development of production cells with regard to physical and cognitive automation: A decade of evolution

This paper will discuss a companys view and evolution of physical and cognitive automation regarding four product families that have been put in production the past decade. The focus of this paper is on the mindset of the production engineers when changing the assembly cells of the products. Results, from observations and interviews, reveal that both the physical and cognitive automation have been considered when designing new assembly cells at the company. Automation has decreased during time covered by the studies. Further, an evolution in lean production and increased involvement of the operators have been in focus during the last two product cell designs, in order to reach recourse and volume flexibility. Moreover, in order to decrease the product complexity, the engineers always design one cell per product family.

Planning in assembly systems — A common modeling for products and resources

This paper presents a method for modeling robot and human resources in the context of assembly systems planning. In assembly systems, several redundant resources can be used to increase system flexibility. However, the “quality” of a sequence planning strongly depends on the “quality” of the system modeling. Furthermore, occurrence of unexpected events or variations in availability of resources may have significant impact on the actual planning. Instead of using simplistic models such as available or unavailable resources, the method presented in this paper proposes a more detailed modeling of resource abilities. Products and resources are considered on the same levels and matched together on a final step. The aim of this modeling is to permit analyses and to increase system flexibility.