The assembly line feeding problem: classification and literature review

In recent years some trends in several product assembly systems emerged, namely mass-customization [Boysen et al., 2007], integration of new product functionalities [Göpfert et al., 2016] and increase in the number of models (e.g. BMW, a German car manufacturer, increased the average number of models offered per year to 37.85 in the period between 2010 and 2016, compared to only 22.3 in the period between 2000 and 2010). These trends have a significant impact on assembly systems since all of them lead to an increasing number of parts required for the final assembly, either by increasing the number of parts required at the border of line (BOL) in general (for new functionalities or new models) or by increasing the number of part variants (mass-customization). Within the assembly line feeding problem (ALFP), the optimal way of supplying assembly stations with parts is examined by assigning different feeding policies to parts. This is mostly based on cost minimizing considerations. The most prevalent line feeding policies are line stocking, kanban, sequencing and kitting [Limere et al., 2015, Sali and Sahin, 2016]. Line stocking and kanban both provide parts in homogeneous filled load carriers. Applying line stocking, a full load carrier (as supplied by the supplier) is provided to the BOL, whereas applying kanban means providing smaller quantities by splitting load carriers into bins. In sequencing and kitting, parts are prepared in the order of demand. In case of sequencing, a container holds variants of one particular component, whereas in case of kitting, different components are grouped and load carriers are filled heterogeneously. The focus of this research is on reviewing literature about the actual ALFP, namely on the assignment of line feeding policies to parts, as well as about related subproblems like e.g. the optimization of milkrun transports within assembly systems. This problem is highly complex due to different decision levels, processes, variable parameters and constraints. In order to help structuring previous and future work, we provide a classification with a three tuple notation as firstly introduced by Graham et al. for machine scheduling [Graham et al., 1979]. Significant decisions and subproblems, occuring in different processes within the ALFP, are classified. This problem includes only in-house logistics and can hence be delimited from external logistics or SCM. Research in this field is becoming more and more attractive to researchers, which can be seen by the rising number of publications. Research is mainly initiated in 1992 [Bozer and McGinnis, 1992] and round about 100 papers are analyzed in this review. The main contribution of this work is twofold. First, we do not only summarize previous research topics but also indicate open research fields, which hopefully motivates researchers to fill the research gaps. Secondly, this work provides, through the classification, a comprehensive framework for researchers to easily identify decisions and subproblems of the ALFP, which can be included in future work

A decision model for kitting

This article gives an overview of the future research directions that will be explored during my PhD. The subject of this research will be parts kitting, or the practice of putting together a collection of components and/or subassemblies that support a certain assembly operation before delivery to the shop floor

Simulation based performance analysis of an end-of-Aisle automated storage and retrieval system

This paper presents and discusses simulation of an End-of-Aisle automated storage and retrieval system, using FLEXSIM 6. The objective of the simulation model is to analyze and compare results of different control policies and physical designs. The performance measures considered for the evaluation of each control policy and layout combination are the total travel time of the crane and the number of storage and retrieval operations performed. The experiments set up and the corresponding results are discussed

An improved largest gap routing heuristic for order picking

The largest-gap policy is a routing heuristic for order picking systems. In this paper we develop an improved largest gap routing method. A simulation approach is used to demonstrate the superior performance of the improved largest gap routing over traditional largest gap. Moreover, this paper tests the performance impact of storage assignment rules on largest gap routings. Several scenarios with various order sizes and different item popularity proportions are tested. Monte-Carlo simulation is used to carry out the experiments. The numerical results from the computational analysis show that our improved largest gap routing always outperforms the traditional largest gap routing, i.e. for all order sizes. The effect is the most distinct when the order size is smaller. Finally the study demonstrates that the optimal storage assignment rule to be combined with largest gap routing is within-aisle storage

Line feeding with variable space constraints for mixed-model assembly lines

Nowadays, assembly systems are used for the assembly of an increasing amount of models, which are often mass-customized to meet customers’ demands. This results in a rising number of parts used for assembly and, consequently, space scarcity at the line. There-fore, parts must not only be fed to the line cost-efficiently, but also meet space constraints (Limère et al., 2015). The assembly line feeding problem (ALFP) deals with the assignment of parts to line feeding policies in order to reduce costs and obtain a feasible solution. Within this paper, we examine all distinct line feeding policies at the same time, namely line stocking, kanban, sequencing and kitting (stationary and traveling kits). There is, to the best of our knowledge, no research conducted, including more than three line feeding policies in a single model (cf. Sali and Sahin, 2016). Furthermore, we assume space at the border of line (BoL) being variable. For this reason, space is not constrained per individual station, but we assume one overall space constraint for the entire line (Hua and Johnson, 2010). The main focus of this work is on accurately modeling the problem. This includes a rep-resentation of all line feeding processes, being storage, preparation, transportation, line side presentation and usage. By incorporating the variable space constraints at the BoL, we pro-vide a decision model reducing the overall costs for line feeding in assembly systems, since rigid space constraints at the BoL usually lead to more expensive line feeding policies. In contrast, variable space constraints enable balancing unequal space usage of different sta-tions, allowing cheaper line feeding policies to be selected. Some preliminary results on the cost impact of variable versus fixed space constraints will be discussed

Using simulation to analyze picker blocking in manual order picking systems

The rise of the e-commerce practice makes the warehouses be confronted with ever smaller orders that must be met ever faster, often within a 24-h period. This pressures the order picking process as the orders pickers' workload becomes higher and higher, leading subsequently to congestion in the warehouse and impacting its productivity. It is therefore crucial to determine which order batching and picking policies enhance the performance of order picking activities. This paper carries out an intensive simulation study to examine the performance of different order picking policies with batching in a wide-aisle warehouse with a low-level picker-to-parts system. The performance of the system is measured in terms of total travelled distance, number of collisions between operators (congestion) and order lead times. A full factorial design is set up and the simulation output is statistically analyzed. The results are reported and thoroughly discussed

In-plant logistics systems modeling with SysML

Up till now Systems Modeling Language (SysML) has mostly been used to model physical systems of interest. This paper shows how SysML can also be used to represent an abstract model. In this application a mathematical cost model is represented using the SysML plugin for the software MagicDraw. ParaMagic, a plugin in MagicDraw supplementary to SysML, links to Mathematica to solve the model. SysML is a formal language and offers a very intuitive graphical representation. It is therefore a useful medium to create a domain specific language for a field of knowledge. The comprehensiveness of the language, which makes it possible to incorporate specification, analysis, design, verification, and validation of systems, makes it a very valuable tool for collaboration on large projects