Design methodology for a hybrid part feeding system in lean-based assembly lines

Abstract

Purpose This paper aims to propose a combined methodology to help decision makers in evaluating and selecting the most effective part feeding system. Design/methodology/approach As a first step of the methodology, a hierarchical clustering analysis is applied to design a kitting or hybrid feeding system. Second, activity-based costing methodology is applied to determine which system is better according to their costs. Besides, sensitivity analysis is implemented to observe the behavior of the system in case of the takt time changes. Findings Using kitting systems purely can lead to problems because of the big and expensive parts in the mixed-model assembly systems. Therefore, the hybrid feeding policy can provide better solutions for such systems. Research limitations/implications A case study is conducted in a company and the most produced product of the company is considered to design the part feeding system. Results indicated that transportation cost has a large proportion on the total cost and the hybrid feeding policy may be a good solution to reduce this cost. Practical implications The paper includes implications for the design of hybrid feeding systems in lean-based assembly lines. The proposed methodology may be a practical tool for decision makers to design and decide on the part feeding policy. Originality/value Kitting design has not been studied yet to the best of the authors’ knowledge. Besides, there is no certain decision methodology indicating which system is better. In this study, different methods are combined as a new methodology with the purpose of industrial decision-making.

SLAE–CPS: Smart Lean Automation Engine Enabled by Cyber-Physical Systems Technologies

“…Jidoka did not gain much attention in the last decade. However, Jidoka is emphasized again due to the rise of Industry 4.0 and is considered a cost-efficient and effective approach for improving system flexibility because of the potential of CPS [ 2 , 3 , 4 , 5 , 8 , 10 , 16 , 17 , 18 , 19 , 20 ].…”

“…A model-view-controller-based architecture is proposed for realizing the interface [ 20 ]. Karadayi et al proposed a design methodology for hybrid feeding systems in lean production-based assembly lines [ 17 ]. MOP methods: Individualized Jidoka solutions are supported by related MOP methods.…”

“…Although Jidoka has recently gained considerable attention in the context of Industry 4.0 [ 2 , 3 , 4 , 5 , 8 , 10 , 16 , 17 , 18 , 19 , 20 ], the following major research questions still exist: CPS-based Jidoka is a hybrid system (physical, conversion, and cyber automation) composed of diverse components, including analog and digital parts, actuators, controllers, ICT, software, and Jidoka rules. CPS-based Jidoka is distributed, such as network-embedded systems that can decouple centralized control and support distributed control.…”

Exploring the application of machine learning to the assembly line feeding problem

“…Some contributions in academic literature have introduced approaches to select the best policy for a given assembly system, starting with Bozer and McGinnis (1992). More recent works have shifted the focus to hybrid feeding policies, i.e., the use of multiple feeding policies in the same assembly system, showing improvements in the overall system performance (e.g., Limère et al 2012;Usta et al 2017). In this direction, the Assembly Line Feeding Problem (ALFP) has been defined as the "unambiguous assignment of every part to a single line feeding policy" (Schmid and Limère 2019).…”

Lean Manual Assembly 4.0: A Systematic Review

“…Looking into minimizing Work-In-Progress stock (WIP) and the required number of assembly operators, pre-kitting offers advantages as well as challenges [134,135]. Usta et al propose a methodology for assessing the best design for part feeding system for Lean assembly, considering that the problems of pure kitting could be countered by hybrid systems (human & machine) [136]. Yamazaki et al present a design method to reduce the cost of flexible automation of material handling systems [137].…”