A Model for Complexity Assessment in Manual Assembly Operations Through Predetermined Motion Time Systems

Journal article

Alkan, B, Vera, D, Ahmad, M, Ahmad, B and Harrison, R (2016). A Model for Complexity Assessment in Manual Assembly Operations Through Predetermined Motion Time Systems. Procedia CIRP. 44, pp. 429-434. https://doi.org/10.1016/j.procir.2016.02.111
AuthorsAlkan, B, Vera, D, Ahmad, M, Ahmad, B and Harrison, R
Abstract

© 2016 The Authors. Manual assembly processes are favoured for supporting low volume production systems, high product variety, assembly operations that are difficult to automate and manufacturing in low-wage countries. However, manual operations can dramatically impact assembly cycle times, quality and cost when the complexity of the manual operation increases. This paper proposes a method for assessing the process complexity of manual assembly operations, using a representation of manual operations based on predetermined motion time systems. The purpose of this framework is to provide a tool that can be used practically to assess, and therefore control, the complexity of manual operations during their design.

KeywordsManual assembly; Task complexity; Complexity management; MODAPTS
Year2016
JournalProcedia CIRP
Journal citation44, pp. 429-434
PublisherElsevier BV
ISSN2212-8271
Digital Object Identifier (DOI)https://doi.org/10.1016/j.procir.2016.02.111
Publication dates
Print2016
Online11 May 2016
Publication process dates
Accepted18 Feb 2016
Deposited30 Jan 2021
Publisher's version
License
File Access Level
Open
Permalink -

https://openresearch.lsbu.ac.uk/item/8vw11

Download files

Publisher's version
1-s2.0-S2212827116003930-main.pdf
License: CC BY-NC-ND 4.0
File access level: Open

  • 126
    total views
  • 99
    total downloads
  • 1
    views this month
  • 1
    downloads this month

Export as

Related outputs

A digital life-cycle management framework for sustainable smart manufacturing in energy intensive industries
Chinnathai, M. and Alkan, B. (2023). A digital life-cycle management framework for sustainable smart manufacturing in energy intensive industries. Journal of Cleaner Production. https://doi.org/10.1016/j.jclepro.2023.138259
A Solution Architecture for Energy Monitoring and Visualisation in Smart Factories with Robotic Automation
Webb, L., Tokhi, M. and Alkan, B. (2023). A Solution Architecture for Energy Monitoring and Visualisation in Smart Factories with Robotic Automation. 26th International Conference on Climbing and Walking Robots and the Support Technologies for Mobile Machines CLAWAR 2023. Florianópolis, Brazil 02 - 04 Oct 2023 CLAWAR Association.
Positional Health Assessment of Collaborative Robots based on Long Short-Term Memory Auto-Encoder (LSTMAE) Network
Hasan, M., Webb, L., Hossain, M., Tokhi, M. and Alkan, B. (2023). Positional Health Assessment of Collaborative Robots based on Long Short-Term Memory Auto-Encoder (LSTMAE) Network. 26th International Conference on Climbing and Walking Robots and the Support Technologies for Mobile Machines CLAWAR 2023. Florianópolis, Brazil 02 - 04 Oct 2023 CLAWAR Association.
Data Driven Machine Learning Model for Condition Monitoring and Anomaly Detection in Power Grids
Saleem, K., Alkan, B. and Dudley-Mcevoy, S. (2023). Data Driven Machine Learning Model for Condition Monitoring and Anomaly Detection in Power Grids. 2023 IEEE Power & Energy Society General Meeting. Orlando, Florida, US 10 - 16 Jul 2023 Institute of Electrical and Electronics Engineers (IEEE).
An End-to-End Big Data Analytics Platform for IoT-enabled Smart Factories: A Case Study of Battery Module Assembly System for Electric Vehicles
Kahveci, S., Alkan, B., Ahmad, M. and Harrison, R. (2022). An End-to-End Big Data Analytics Platform for IoT-enabled Smart Factories: A Case Study of Battery Module Assembly System for Electric Vehicles. Journal of Manufacturing Systems. 63, pp. 214-223. https://doi.org/10.1016/j.jmsy.2022.03.010
A Hybrid Extreme Learning Machine Model with Harris Hawks Optimisation Algorithm: An Optimised Model for Product Demand Forecasting Applications
Chaudhuri, K. D. and Alkan, B. (2022). A Hybrid Extreme Learning Machine Model with Harris Hawks Optimisation Algorithm: An Optimised Model for Product Demand Forecasting Applications. Applied Intelligence. https://doi.org/10.1007/s10489-022-03251-7
Performance Comparison of Recent Population-based Metaheuristic Optimisation Algorithms in Mechanical Design Problems of Machinery Components
Alkan, B. and Chinnathai, M.K. (2021). Performance Comparison of Recent Population-based Metaheuristic Optimisation Algorithms in Mechanical Design Problems of Machinery Components. MDPI Machines. 9 (12), p. 341.
A novel data-driven approach to support decision-making during production scale-up of assembly systems
Alkan, B. (2021). A novel data-driven approach to support decision-making during production scale-up of assembly systems. Journal of Manufacturing Systems. 59, pp. 577-595. https://doi.org/10.1016/j.jmsy.2021.03.018
Identifying Optimal Granularity Level of Modular Assembly Supply Chains Based on Complexity-Modularity Trade-Off
Alkan, B., Bullock, S. and Galvin, K. (2021). Identifying Optimal Granularity Level of Modular Assembly Supply Chains Based on Complexity-Modularity Trade-Off. IEEE Access. 9, pp. 57907 - 57921. https://doi.org/10.1109/ACCESS.2021.3072955
Assessing operational complexity of manufacturing systems based on algorithmic complexity of key performance indicator time-series
Alkan, B. and Bullock, S. (2020). Assessing operational complexity of manufacturing systems based on algorithmic complexity of key performance indicator time-series. Journal of the Operational Research Society. https://doi.org/10.1080/01605682.2020.1779622
A Design Process Framework to Deal with Non-functional Requirements in Conceptual System Designs
Alkan, B., Seth, B., Galvin, K. and Johnson, A. (2020). A Design Process Framework to Deal with Non-functional Requirements in Conceptual System Designs. Complex Systems Design & Management. Paris 15 - 17 Dec 2020
Improving just-in-time delivery performance of IoT-enabled flexible manufacturing systems with AGV based material transportation
Yao, F, Alkan, B, Ahmad, B and Harrison, R (2020). Improving just-in-time delivery performance of IoT-enabled flexible manufacturing systems with AGV based material transportation. Sensors (Switzerland). 20 (21), pp. 1-25. https://doi.org/10.3390/s20216333
A framework to predict energy related key performance indicators of manufacturing systems at early design phase
Assad, F, Alkan, B, Chinnathai, MK, Ahmad, MH, Rushforth, EJ and Harrison, R (2019). A framework to predict energy related key performance indicators of manufacturing systems at early design phase. Procedia CIRP. 81, pp. 145-150. https://doi.org/10.1016/j.procir.2019.03.026
A Framework for Pilot Line Scale-up using Digital Manufacturing
Chinnathai, M. K., Al-Mowafy, Z., Alkan, B., Vera, D. and Harrison, R. (2019). A Framework for Pilot Line Scale-up using Digital Manufacturing. Procedia CIRP. 81, pp. 962-967. https://doi.org/10.1016/j.procir.2019.03.235
An experimental investigation on the relationship between perceived assembly complexity and product design complexity
Alkan, B. (2019). An experimental investigation on the relationship between perceived assembly complexity and product design complexity. International Journal on Interactive Design and Manufacturing (IJIDeM). 13 (3), pp. 1145-1157. https://doi.org/10.1007/s12008-019-00556-9
A virtual engineering based approach to verify structural complexity of component-based automation systems in early design phase
Alkan, B. and Harrison, R. (2019). A virtual engineering based approach to verify structural complexity of component-based automation systems in early design phase. Journal of Manufacturing Systems. 53, pp. 18-31. https://doi.org/10.1016/j.jmsy.2019.09.001
Pilot To Full-Scale Production: A Battery Module Assembly Case Study
Chinnathai, M.K., Alkan, B., Vera, D. and Harrison, R. (2018). Pilot To Full-Scale Production: A Battery Module Assembly Case Study. Procedia CIRP. 72, pp. 796-801. https://doi.org/10.1016/j.procir.2018.03.194
Proposing a Holistic Framework for the Assessment and Management of Manufacturing Complexity through Data-centric and Human-centric Approaches
Alkan, B. (2018). Proposing a Holistic Framework for the Assessment and Management of Manufacturing Complexity through Data-centric and Human-centric Approaches. Proceedings of the 3rd International Conference on Complexity, Future Information Systems and Risk (COMPLEXIS 2018).
Complexity in manufacturing systems and its measures: a literature review
Alkan, B., Vera, D., Ahmad, M., Ahmad, B. and Harrison, R. (2018). Complexity in manufacturing systems and its measures: a literature review. European Journal of Industrial Engineering . 12 (1). https://doi.org/10.1504/EJIE.2018.089883
Convertibility Evaluation of Automated Assembly System Designs for High Variety Production
Chinnathai, M.K., Alkan, B. and Harrison, R. (2017). Convertibility Evaluation of Automated Assembly System Designs for High Variety Production. Elsevier BV. https://doi.org/10.1016/j.procir.2017.01.005
Assessing Complexity of Component-Based Control Architectures Used in Modular Automation Systems
Alkan, B., Vera, D., Chinnathai, M. K. and Harrison, R. (2017). Assessing Complexity of Component-Based Control Architectures Used in Modular Automation Systems . International Journal of Computer and Electrical Engineering . 9 (1). https://doi.org/10.17706/ijcee.2017.9.1.393-402
A method to assess assembly complexity of industrial products in early design phase
Alkan, B., Vera, D., Ahmad, B. and Harrison, R. (2017). A method to assess assembly complexity of industrial products in early design phase. IEEE Access. 6, pp. 989-999. https://doi.org/10.1109/ACCESS.2017.2777406
A Framework for Automatically Realizing Assembly Sequence Changes in a Virtual Manufacturing Environment
Ahmad, M, Ahmad, B, Harrison, R, Alkan, B, Vera, D, Meredith, J and Bindel, A (2016). A Framework for Automatically Realizing Assembly Sequence Changes in a Virtual Manufacturing Environment. Elsevier BV. https://doi.org/10.1016/j.procir.2016.04.178
A Lightweight Approach for Human Factor Assessment in Virtual Assembly Designs: An Evaluation Model for Postural Risk and Metabolic Workload
Alkan, B, Vera, D, Ahmad, M, Ahmad, B and Harrison, R (2016). A Lightweight Approach for Human Factor Assessment in Virtual Assembly Designs: An Evaluation Model for Postural Risk and Metabolic Workload. Elsevier BV. https://doi.org/10.1016/j.procir.2016.02.115
Hydrogen Fuel Cell Pick and Place Assembly Systems: Heuristic Evaluation of Reconfigurability and Suitability
Ahmad, M., Ahmad, B., Alkan, B., Vera, D., Harrison, R., Meredith, J. and Bindel, A. (2016). Hydrogen Fuel Cell Pick and Place Assembly Systems: Heuristic Evaluation of Reconfigurability and Suitability. Procedia CIRP. 57, pp. 428-433. https://doi.org/10.1016/j.procir.2016.11.074
The Use of a Complexity Model to Facilitate in the Selection of a Fuel Cell Assembly Sequence
Ahmad, M., Alkan, B., Ahman, B., Vera, D., Harrison, R., Meredith, J. and Bindel, A. (2016). The Use of a Complexity Model to Facilitate in the Selection of a Fuel Cell Assembly Sequence. Procedia CIRP. 44, pp. 169-174. https://doi.org/10.1016/j.procir.2016.02.054
Design Evaluation of Automated Manufacturing Processes Based on Complexity of Control Logic
Alkan, B., Vera, D., Ahmad, M., Ahmad, B. and Harrison, R. (2016). Design Evaluation of Automated Manufacturing Processes Based on Complexity of Control Logic. Procedia CIRP. 50, pp. 141-146. https://doi.org/10.1016/j.procir.2016.05.031