A simulation based decision support approach for operational capacity planning in a customer order driven assembly line

Andersson, M.; Olsson, G.

doi:10.1109/wsc.1998.745793

Cited by 18 publications

(17 citation statements)

References 6 publications

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“…This type of simulation presumes that simulation models are highly detailed they have a longer lifetime than models from traditional simulation studies [43]. Furthermore, they demand that the effort to update the model in accordance with the real system can be done in a time and cost effective way [43].…”

Section: ) Motivationmentioning

confidence: 99%

“…For this reason, many authors mention the necessity to improve the efficiency in these areas (e.g., [40] and [43]- [45]). In literature especially two approaches are being discussed:…”

Section: ) Motivationmentioning

confidence: 99%

“…The first aspect is discussed for example in [46]. Aderson and Olsson [43] use a standard discrete event simulation package for supporting operational decisions regarding daily labor assignment in a customer-driven assembly line. The information for building the simulation model is gathered by interviews and time data collections.…”

Section: ) Motivationmentioning

confidence: 99%

See 2 more Smart Citations

Artificial Cognition in Production Systems

Bannat¹,

Bautze²,

Beetz³

et al. 2011

IEEE Trans. Automat. Sci. Eng.

103

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Abstract-Today's manufacturing and assembly systems have to be flexible to adapt quickly to an increasing number and variety of products, and changing market volumes. To manage these dynamics, several production concepts (e.g., flexible, reconfigurable, changeable or autonomous manufacturing and assembly systems) were proposed and partly realized in the past years. This paper presents the general principles of autonomy and the proposed concepts, methods and technologies to realize cognitive planning, cognitive control and cognitive operation of production systems. Starting with an introduction on the historical context of different paradigms of production (e.g., evolution of production and planning systems), different approaches for the design, planning, and operation of production systems are lined out and future trends towards fully autonomous components of an production system as well as autonomous parts and products are discussed. In flexible production systems with manual and automatic assembly tasks, human-robot cooperation is an opportunity for an ergonomic and economic manufacturing system especially for low lot sizes. The state-of-the-art and a cognitive approach in this area are outlined. Furthermore, introducing self-optimizing and self-learning control systems is a crucial factor for cognitive systems. This principles are demonstrated by a quality assurance and process control in laser welding that is used to perform improved quality monitoring. Finally, as the integration of human workers into the workflow of a production system is of the highest priority for an efficient production, worker guidance systems for manual assembly with environmentally-and situationally dependent triggered paths on state-based graphs are described in this paper.Note to Practitioners-Today's manufacturing enterprises have to face a number of challenges in a turbulent environment that originates amongst other from saturated markets, unprecedented and abrupt changes in market demands, an ever increasing number of product variants and smaller lot sizes. A recent research trend in Germany is the so called Cognitive Factory, where artificial cognitive capabilities are introduced to the control of production systems. The applications range from production planning and control, human-robot-cooperation, automatic robot programming to intuitive worker guidance systems.The concept of fully automated production systems is no longer a viable vision, as it has been shown, that the conventional automa- tion is not able to deal with the ever-rising complexity of modern production systems. Especially, a high reactivity, agility and adaptivity that is required by modern production systems, can only be reached by human operators with their immense cognitive capabilities, which enable them to react to unpredictable situations, to plan their further actions, to learn and to gain experience and to communicate with others. Thus, new concepts are required, that apply these cognitive principles to the planning processes and control systems of pr...

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Section: ) Motivationmentioning

confidence: 99%

“…For this reason, many authors mention the necessity to improve the efficiency in these areas (e.g., [40] and [43]- [45]). In literature especially two approaches are being discussed:…”

Section: ) Motivationmentioning

confidence: 99%

See 1 more Smart Citation

Artificial Cognition in Production Systems

Bannat¹,

Bautze²,

Beetz³

et al. 2011

IEEE Trans. Automat. Sci. Eng.

103

View full text Add to dashboard Cite

show abstract

“…First, workflow of the facility depends on performance of individual workers with various levels of experience. Second, absenteeism of workers due to personal reasons can increase the complexity of labor allocation (Andersson and Olsson, 1998). Third, seasonal demand for transplants makes the resource (i.e., both workers and other supplies) allocation of production lines complicated.…”

mentioning

confidence: 99%

Evaluation of Simulation-Based Optimization in Grafting Labor Allocation

Masoud

Son²,

Kubota

et al. 2018

Applied Engineering in Agriculture

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“…Typical FMS applications of simulation are: 4 1. Evaluate the system performance of alternative designs and the effectiveness of alternative operating policies.…”

Section: Introductionmentioning

confidence: 99%

Modeling and Analysis of Flexible Manufacturing Systems: A Simulation Study

Chang¹,

Peterson²

2015 ASEE Annual Conference and Exposition Proceedings

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Flexible Manufacturing Systems (FMS) are highly modular reconfigurable systems, consisting of a group of processing workstations (such as CNC machining centers), and interconnected by an automated material handling and storage system. The adoption of a Flexible Manufacturing System involves a substantial investment and a high degree of uncertainty for today's factories. With the aim of combining production flexibility and productivity, the design decisions of a flexible manufacturing system must be based on FMS system performance. The current literature does not, however, provide enough detail to analyze the system performance in a Flexible Manufacturing System with different layout configurations. Models based on discreteevent simulation can be utilized to design production systems such as FMSs. In this study, ProModel software is used to simulate different models and evaluate the system performance in different FMS layouts. Based on the simulation models, we investigated the effectiveness and efficiency of FMS including system performance metrics such as manufacturing lead time (MLT), resource utilization, inventory and queue levels, throughput, bottleneck analysis, and the number of workstations. These decisions of FMS design are critical and need to be investigated in the initial phase with extreme care ensuring that the designed FMS will successfully fulfill the demands of a fluctuating market. Finally, this paper presents a case problem for performance evaluation of an existing manufacturing system. The result shows that the simulation models can effectively help the users to rapidly response to a mix of part styles and changes of demand patterns.

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A simulation based decision support approach for operational capacity planning in a customer order driven assembly line

Cited by 18 publications

References 6 publications

Artificial Cognition in Production Systems

Artificial Cognition in Production Systems

Evaluation of Simulation-Based Optimization in Grafting Labor Allocation

Modeling and Analysis of Flexible Manufacturing Systems: A Simulation Study

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