By reviewing and classifying literature on the ALFP, we discovered large research gaps. Hereafter, we give an overview of the, to our perception, most substantial open research areas. Firstly, we describe research opportunities within the framework of the proposed ALFP classification, in Subsection 2.5.1. Secondly, we propose related research streams or possible integrations in Subsection 2.5.2.
2.5.1 Extending the ALFP
Line feeding policies
In practice, the implementation of each line feeding policy is possible for every assembly system.
Thus, it is extremely important to evaluate the benefits and drawbacks of all line feeding policies by comparing them with each other.
In most cases, except from Schmid et al. (2018), only two or three line feeding policies are taken into account as can be seen in Table 2.5. This holds true for qualitative and quantitative comparisons. Distinguishing stationary and traveling kits, future research should compare five line feeding policies (α1) in order to make them easily comparable and creating managerial insights. For creating managerial insights, it might be interesting to investigate the effect of all possible different costs on decision making. Doing this, it can be found which costs are actually relevant and should be incorporated in future decision making. Costs with high differences for different line feeding policies are especially promising to have strong effects on decision making.
Quality costs, e.g., could differ largely for different line feeding policies and might therefore influence decision making.
Product model characteristics
As mentioned in the introduction of this chapter, trends like mass customization can be observed in product assembly, leading to an increased use of mixed and multi model assembly lines. This can also be seen in the case studies reviewed for the classification. Though these trends are prevalent in industry, only one research paper was found providing a mathematical model explic-itly dealing with the feeding problem for multi model assembly lines or mixed model assembly lines with models having distinct precedence graphs (α2) (Schmid et al., 2018). However, dis-tinct precedence graphs will lead to a higher number of kits, since there will be different kits established for different models. Additionally, in multi model assembly lines some particularities, like feeding of assembly lines in intervals can be considered. These intervals can, e.g., depend on the size of production lots. Battini et al. (2010a) mention a few rules of thumb on feeding multi model lines. However, no mathematical model for distinct mixed and multi model assembly lines, neither optimization, nor description, has been formulated. Therefore, it still is an open field for research.
Stochastic demand
In reality, product and part demand (α4) are deterministic only in a short perspective. But as the ALFP is a more long-termed, tactical decision demand cannot be known exactly. Several further possible reasons are demand volatility, part quality, rescheduling, and product change.
Variability of demand may lead to manifold difficulties in a feeding system, such as an unbalanced usage of transportation or storage capacities. Furthermore, variability also has an impact on the amount of stock that is needed in an assembly system. At this point, only Faccio (2014) and Bukchin and Meller (2005) analyzed the influence of variable demand by showing the impact on line feeding policy selection and space allocation, respectively. To summarize, the influence of variable demand on the ALFP under varying circumstances is still not fully explored and should be enriched by further research.
Configuration versus reorganization
As described in Section 2.2.4, decisions are usually taken in a hierarchical order. This applies to decisions from different hierarchical levels but also to decisions from within a single hierarchical decision levels. Arrangement of storage (β1) and planning of transportation and used equipment (β3) as well as design of the preparation areas (β2) are vivid examples of decisions at the same level as the ALFP. In most papers (see Table 2.5), these decisions are assumed to be taken before the assignment of line feeding policies. Within this approach, existing systems are typically reorganized and improved, than designed. As described by Sternatz (2015), decisions on line feeding should be taken in advance of the start of production. Therefore, further research should aim towards a simultaneous optimization of feeding and other design decisions. A first step towards this is done by Battini et al. (2010a) integrating the determination of the number of supermarkets and assignment of line feeding policies. However, this approach is still stepwise and more logic based rather than optimised.
Return process
A promising research field is the exploration of the return process (β4) in the context of assembly line feeding. As aforementioned in Section 2.3.2, most authors simply assume that returning depleted load carriers is integrated in the feeding process. Determining situations, in which it is useful to separate feeding and return, is a challenge for future research. Additionally, configuration and control of such separated return processes need to be explored.
Ergonomics
As musculo-skeletal disorders are an increasing societal problem in many countries, companies aim to reduce or redistribute the ergonomic load on their workers. As assembly line feeding traditionally includes a lot of manual activities, it is worthwhile to investigate ergonomics further.
Especially the combination of ergonomics and multiple line feeding policies seems relevant, as the way of providing material to the assembly worker heavily impacts the ergonomic load (Hanson
and Medbo, 2016a). However, integrating ergonomics into assembly line feeding should not be limited only to the assembly worker but also be extended to logistical workers.
Operation times
The investigation of operation times for the assembly worker (β5) is another auspicious field.
Lim`ere et al. (2015), e.g., utilize dynamic walking distances for operators in the system at the BoL as well as in the preparation area. A similar approach can be seen at Schmid et al.
(2018). As reported by Sali and Sahin (2016) and Schmid et al. (2018) it is hard to give good approximations for operation times, and especially walking as the level of detail is not sufficient.
Therefore, assigning parts to specific locations might resolve this issue.
Another relevant issue is the investigation of cycle time restrictions as proposed by Sali and Sahin (2016). As reasoned by Sternatz (2015), an integration of assembly line balancing and line feeding is relevant, as in practice the decisions for line feeding are only taken when assembly lines are balanced. Thus, optimization models, that do not integrate both aspects should take into account that the available time for assembly operations is limited, which should be tackled by a constraint ensuring feasibility.
Stocks in the feeding system
Mostly, objective functions aim at reducing costs. These costs can be a sum of various cost elements as described in the γ-field of the classification. Lim`ere et al. (2012), e.g., claim that holding costs of parts at the BoL should not be considered, because it can be assumed that the overall inventory of parts in an assembly system is constant, irrespective of the line feeding policy. Therefore, only the location of storage will differ with respect to the line feeding policy.
Sali et al. (2015) on the other hand, assume that holding costs for parts at the BoL should be considered in the form of opportunity costs, whereas holding costs for parts in storage areas are neglected. These different assumptions call for an exploration of realistic assumptions on parts’
inventory and the respective holding costs within an assembly system. Utilizing multi echelon concepts, stocks seem to differ according to the number of storage areas, which in turn depend on the line feeding policy. Moreover, Hanson and Finnsgard (2014) describe a case company, storing an additional pallet close to the BoL in order to compensate demand variability, if line stocking is applied. Stock amounts in a system might also depend on production control and the respective parameterization. E.g., if some line feeding policies are controlled by a pull production control system using Kanban cards the number of cards and the size of containers might have an influence on stocks in a systems. In summary, the effect of line feeding design on stocks in the system is unclear and demands for investigation.
2.5.2 Integrating additional aspects with the ALFP
Assembly line feeding scheduling
Operationally scheduling the feeding problem of assembly lines is closely related to the assignment of line feeding policies. As raised in this review, the literature on scheduling part transportation is broad. Yet it is just one out of three processes of the ALFP that may be scheduled in an integrated manner. In fact, assembly line feeding scheduling includes the whole process of replenishment of preparation areas (Emde, 2017), preparation itself and transportation of parts.
A possible objective function is, e.g., meeting due dates for part replenishment to avoid stockouts at the assembly line. Those processes could be scheduled in a reverse manner, starting from the demand date and scheduling the preceding processes in a similar way to the line traveling repairman problem (TRP), which is described by Bock (2015). The TRP describes scheduling repair operations with request deadlines and general processing times. This resembles the demand due date of assembly line feeding that should not be missed under consideration of varying processing times for operations like preparation, transportation loading and unloading.
The actual operations might be affected by new technologies, such as fluid logistics, robotic vision used for automated picking or drones used for urgent deliveries. The control of these systems could be taken into account when line feeding for real-time demand is scheduled.
Decision levels
As already mentioned above, decisions of different levels are taken in a hierarchical manner.
Examining the strategic outsourcing decision simultaneously with the tactical ALFP seems to be a promising new research area, by which the outsourcing decision can be supported in a quantitative manner.
In addition, more operational aspects like scheduling can also be combined with assembly line feeding by solving the line feeding problem and the line feeding scheduling simultaneously. Andr´es et al. (2008), e.g., connected the balancing and sequencing of assembly lines. This approach can be transferred to assembly line feeding and feeding scheduling as partly mentioned in the classification for the scheduling of preparation and/or transportation processes.
Line Balancing
In an assembly system, the assembly line balancing problem (ALBP) and assembly line feeding problem are the most influential problems, affecting the system’s performance. Usually, an as-sembly line is configured by solving the ALBP first, as described by Boysen et al. (2007), and afterwards the assembly line feeding problem is solved (Sternatz, 2015). Both problems com-prise the configuration of the assembly system and hence, belong to the same decision level. As already proposed by Sternatz (2015) and Battini et al. (2016a), the integration of the highly interdependent problems of line balancing and feeding should be tackled. In the former pa-per, balancing and feeding are considered for a mixed model assembly system with isomorphic precedence graphs, whereas in the latter paper, line balancing, line feeding and ergonomics are
modelled for a single product assembly system.
Balancing and feeding both also have operational aspects, described within this paper as assembly line scheduling and line feeding scheduling. In the field of assembly line scheduling, there is already a broad literature (Boysen et al., 2009), whereas no literature on line feeding scheduling could be found. It is easy to see that the interaction of ALBP and ALFP, as already shown by Sternatz (2015), also has an impact on the operational scheduling level, since the tactical decisions affect their respective operational problems and vice versa. Therefore, operational decisions of scheduling problems may be treated in an integrated ALBP and ALFP formulation.
General manufacturing feeding
The main focus of this study is feeding material to assembly lines. Assembly lines are charac-terized by the way how workpieces are transported through the manufacturing area and by the tasks performed which can usually be described byjoining operations like welding or screwing (e.g. DIN 8580). However, generally speaking, products can be manufactured in multiple ways, including molding, forming or machining. These manufacturing processes are usually organized differently, in job shops or work cells. Aside from a different process, there might be a differ-ence in the kinds of goods used in other manufacturing systems like, e.g., liquids or bulk goods.
Provision of material in these manufacturing types might also be an issue to address in future research. Therefore, firstly the differences of these systems should be investigated and, secondly, approaches for assembly lines have to be adapted to those other manufacturing types.