(Mt) – Article Review: Flexibility planning in global inbound logistics

Availableonline online atwww.sciencedirect.com www.sciencedirect.com Available Availableatonline at www.sciencedirect.com ScienceDirect ScienceDirect ScienceDirect ProcediaCIRP CIRP00 79(2017) (2019)79 415–420 Procedia 000–000 Procedia CIRP (2019) 415–420 www.elsevier.com/locate/procedia www.elsevier.com/locate/procedia 12th CIRP Conference on Intelligent Computation in Manufacturing Engineering, 18-20 July 2018, Gulf of Naples, Italy 28th CIRP Design Conference, May 2018, Nantes, France Flexibility planning in global inbound logistics A new methodology to analyze thea, functional and physical architecture of Sarah Fink *, Franziska Benzb existing productsTechnical for an assembly oriented product family identification University Dortmund, Emil-Figge-Straße 50, 44227 Dortmund, Germany a Munich University of Applied Sciences, Lothstraße 64, 80335 Munich, Germany b Paul Stief *, Jean-Yves Dantan, Alain Etienne, Ali Siadat * Corresponding author. Tel.: +49-151-601-59283; E-mail address: sarah.fink@tu-dortmund.de École Nationale Supérieure d’Arts et Métiers, Arts et Métiers ParisTech, LCFC EA 4495, 4 Rue Augustin Fresnel, Metz 57078, France *Abstract Corresponding author. Tel.: +33 3 87 37 54 30; E-mail address: paul.stief@ensam.eu Building on the variety of different methods to operationalize flexibility in supply chains, this paper presents a process-oriented approach for the measurement and planning of inbound logistics flexibility in global production networks. Using the automotive industry as an example, process Abstract sequences of the overseas supply like transportation, storing or handling are parameterized regarding their respective flexibility range as well as the time- and cost-related implications of their adjustment. On this basis, a model to evaluate benefits and costs associated with the investment Inintoday’s environment, the trend towards morethe product variety andprocess customization is unbroken. this development, the need of logisticsbusiness flexibility can be derived in order to support decision-making for a rolling planningDue on atotactical level. agile and reconfigurable production systems emerged to cope with various products and product families. To design and optimize production Authors. Published B.V. matches, product analysis methods are needed. Indeed, most of the known methods aim to © 2019 as The Elsevier B.V. systems well as to choose theby optimal product Peer-review underorresponsibility responsibility the committee of Conference Intelligent Computation ininManufacturing Peer-review under of the scientific scientific committee of the the 12th 12thCIRP CIRP Conference on Intelligent Computation Manufacturing Engineering. analyze a product one product of family on the physical level. Different product families,on however, may differ largely in terms of theEngineering. number and nature of components. This fact impedes an efficient comparison and choice of appropriate product family combinations for the production Keywords: Global inbound logistics; Supply chain flexibility; Logistics flexibility; Flexibility operationalization; Flexibility planning; Automotive industry system. A new methodology is proposed to analyze existing products in view of their functional and physical architecture. The aim is to cluster these products in new assembly oriented product families for the optimization of existing assembly lines and the creation of future reconfigurable assembly systems. Based on Datum Flow Chain, the physical structure of the products is analyzed. Functional subassemblies are identified, and a1.functional analysis is performed. Moreover, a hybrid functional and physical architecture graph (HyFPAG) is the output logistics which depicts the Introduction From an integrative perspective, inbound systems similarity between product families by providing design support to both, production system planners and product designers. An illustrative include several vehicle projects at various nodes and edges of example of a nail-clipper is used to explain the proposed methodology. An industrial case study on two product families of steering columns of Parts logistics in the automotive industry encompasses all a globally expanded network. Especially international thyssenkrupp Presta France is then carried out to give a first industrial evaluation of the proposed approach. from components provided logistical chains are subject to unforeseen fluctuations with ©processes 2017 The Authors. Published bybeing Elsevier B.V. by suppliers to their final presentation at the production line of an Original challenging consequences. Peer-review under responsibility of the scientific committee of the 28th CIRP Design Conference 2018. In order to ensure stable supply Equipment Manufacturer (OEM). It can be divided into delivery of parts from a supplier’s facility to an OEM’s plant, in-house logistics, responsible for all processes from goods receipt to assembly and reverse logistics, comprising the return of unused 1.materials Introduction [1]. The design of these processes takes place before Start of Due to (SOP) the of fast development the domain of Production a vehicle project andinpre-defines the scope communication and an ongoing trend of digitization and of action for the series. Focusing on external inbound logistics, digitalization, enterprises are facing this includes manufacturing long-term strategic decisions for theimportant network challenges in today’s market environments: a of continuing structure like location selection or layout design logistics tendency reduction of tactical productlevel development and facilities.towards On a medium-term of severaltimes months, shortened product lifecycles. In addition, there is an increasing choices regarding the planning of area, inventory or human demand oforcustomization, at the concepts same time a global resources the selection ofbeing part-based forin packaging, competition with competitors all over the world. This delivery and transportation are made. On an operational trend, level, which is inducing to micro logistical processesthe anddevelopment the use of from relatedmacro structures and markets, in diminished due to augmenting resourcesresults are finalized during lot thesizes ramp-up phase, shortly product varieties (high-volume production) [1]. before the first car is produced to [2,low-volume 3]. To cope with this augmenting variety as well as to be able to identify possible optimization potentials in the existing production system, it is important to have a precise knowledge external Assembly; inbound Design logistics, concentrating on the Keywords: method; Family identification under varying conditions, external inbound logistics must be capable of acting beyond initially determined boundaries. In this paper, logistics flexibility, as one dimension of supply chain flexibility, is discussed with a process-based view, including multiple network stages from a multi-project of the product range and characteristics and/or perspective. Building on existing research,manufactured an approach for the assembled in this system. In this context, the main challenge in measurement and continuous planning of logistics flexibility modelling and analysis is now not only to cope with single on a tactical level is deducted. products, a limited product range or existing product families, but also to beFlexibility able to analyze and toChain compare products to define 2. Logistics in Supply Flexibility new product families. It can be observed that classical existing product families are regrouped in function 2.1. Challenges in global supply chains of clients or features. However, assembly oriented product families are hardly to find. On the product family islevel, products mainly in two International logistics defined as thediffer sum of all activities main characteristics: (i) the number of components and (ii) the for planning and realizing cross-border logistics processes [4]. type of components (e.g. mechanical, electrical, electronical). In the context of long supply chains, logistical networks are Classical methodologies considering mainlyThe single products highly interconnected, complex and dynamic. coordination or solitary, already existing product families analyze the of simultaneous processes, serving to ensure the effective product structure on a physical level (components level) which causes difficulties regarding an efficient definition and comparison of different product families. Addressing this 2212-8271©© ©2017 2019The The Authors. Published by Elsevier 2212-8271 2019 The Authors. Published byElsevier Elsevier B.V.B.V. 2212-8271 Authors. Published by B.V. Peer-reviewunder underresponsibility responsibility the scientific committee of 12th CIRP Conference on 2018. Intelligent Computation in Manufacturing Engineering. Peer-review under responsibility the scientific committee ofthe thethe 12th CIRP Conference on Intelligent Computation in Manufacturing Engineering. Peer-review ofofof the scientific committee of 28th CIRP Design Conference 10.1016/j.procir.2019.02.114 10.1016/j.procir.2019.02.114 416 416 Sarah Fink et al. / Procedia CIRP 79 (2019) 415–420 Sarah Fink et al. / Procedia CIRP 79 (2019) 415–420 delivery of products to the right place, at the right time, in the right quantity, quality and order in a cost-efficient manner, is a demanding task [5]. In contrast to domestic supply chains, international and cross-border flow of goods has to face particular procedural as well as country-specific conditions. While the former refers to long transportation distances or higher order lead times, the latter includes macro- and microeconomic aspects in the target market [3, 4, 5, 6]. The resulting challenges are reflected in the complexity of the network in terms of the number of and distance between suppliers and customers, which affects strategic decisions in particular. Furthermore, demand uncertainties like fluctuations in volume, represented in the varying amount of ordered goods, changes in product mix in form of the composition of an offer, the frequent introduction of new products, the related increase of product customization as well as the need to meet subsequent changes in demand affect medium-term decisions on a planning level. Process-related uncertainty like the necessity to handle wrong, missing or damaged parts as well as process disruption can occur within a short time [7, 8, 9, 10, 11]. In this environment, flexibility can be seen as an important ability of a supply chain in order to cope with changing internal and external conditions to ensure reliable performance [12, 13, 14, 15, 16]. 2.2. Management of flexibility in supply chains Flexibility is a multi-dimensional, complex, polymorph and hard-to-capture construct [17, 18]. Building on research on the flexibility of manufacturing systems, the scientific discourse extended its consideration from one single unit to the flexibility of various components and sub-components of a whole supply chain [15, 17], where intra- and inter-organizational capabilities of all elements from the shop floor to the network are included [9, 12, 13, 15]. Since supply chain flexibility can be seen as a characteristic that generates both benefit and effort, its appropriate application is necessary for a system’s effective and efficient operation. The management of supply chain flexibility deals with the alignment of actual and required flexibility. Generally, it encapsulates five phases. The identification phase clarifies required flexibility as the amount of change needed to respond properly, and actual flexibility as the existing capability of all chain elements to change. In the following operationalization phase the required and actual flexibility are displayed numerically, both of which can be scaled according to their potential. During the planning phase, the comparison of the given and necessary scope of action is deducted. If a gap between required and actual flexibility potential occurs, a flexibility measure needs to be identified in order to counterbalance the difference. Thereby, the benefit and cost of a flexibility measure need to be evaluated. By doing so, the assumption of its application leads to a theoretically assumed adjusted flexibility potential in form of an increase or reduction. During the adjustment phase, the flexibility potential is modified in the real system by the implementation of a flexibility measure. Within the utilization phase, the adjusted flexibility potential is actually claimed [10, 14, 16, 19, 20]. 2.3. Measuring supply chain flexibility Regarding the operationalization of supply chain flexibility, one group of approaches aims to provide a key performance indicator for flexibility [21, 22, 23], while others deduct statistical models, where flexibility is demonstrated as a latent construct, represented by various manifest indicators [8, 24]. Further methods are inspired by real options, where the value of an investment in flexibility takes the probability of occurrence of its need into account [20, 25]. As mentioned above, in the context of flexibility planning, a supply chain can be scaled by the flexibility potential of all relevant components [14]. Within the research on manufacturing systems, Slack (1983) describes flexibility by two dimensions, the range of state a system or resource is capable to achieve and the response, as the ease in terms of cost and time by which these changes can be made [26]. Upton (1994) added uniformity as a constituting element of flexibility, which demands to maintain a system’s performance while varying between different states [27]. Although these dimensions could be modeled for various areas of application, only a few approaches have already adopted this differentiation in the context of supply chain flexibility [14, 28]. 2.4. Planning of supply chain flexibility Current research has recognized that the associated costs of flexibility have to be compared with its tangible and intangible benefits. In this context, empirical evidence for the direct or moderated effect of supply chain flexibility on financial measures like return on investment, return on sales and market share [11, 29] as well as on non-financial performance like customer satisfaction and customer loyalty has been found [24, 30, 31]. Nevertheless, only a few planning models, confronting the trade-off between the effort and benefit of supply chain flexibility can be identified. Aprile et al. (2005) have developed an optimization model aiming to minimize lost sales under product- and production-related uncertainty by considering flexibility of several supply chain elements [32]. Chan and Chan (2010) use agent-based simulation to indicate that flexibility within a supply chain can positively influence performance by improving the customer demand fill rate and by simultaneously considering several cost categories under varying demand and supply [33]. Schütz and Tomasgard (2011) present a two-stage stochastic programming model and include flexibility in volume, delivery and operational decision, facing demand uncertainty. Unsatisfied demand is modeled either as backlog, allowing to shift deliveries into a subsequent period, or as lost sales, which is penalized with a shortfall cost equal to 25 percent of a product’s market price [34]. Esmaeilikia et al. (2016) describes a tactical supply chain model which incorporates options in sourcing, manufacturing and logistics for flexibility adjustment. On the one hand, each option relates to rising costs, on the other hand it contributes to customer service in the form of avoided backlog [35]. Sarah Fink et al. / Procedia CIRP 79 (2019) 415–420 Sarah Fink et al. / Procedia CIRP 79 (2019) 415–420 2.5. Logistics flexibility within supply chain flexibility From a horizontal point of view, supply chain flexibility can be divided into constituting dimensions like product development flexibility, sourcing flexibility, production flexibility or logistics flexibility [9, 24]. Thereby, logistics flexibility enables a supply chain to adjust to changing conditions in inbound and outbound delivery as well as in support and services [13, 24]. It is achieved by the adjustment of the flow of material and related information, from the point of origin to the destination [24]. Focusing on the physical constituent part of logistics flexibility, this ability includes flexibility of processes like transportation, storing and handling as well as the related support processes like packing or commissioning. On a tactical level, flexibility in transportation includes the ability to change the mode, route or carrier of transportation, the transport capacity or frequency and the ability to conduct express delivery [12, 13, 14, 24, 35, 36, 37]. For storage processes, logistics flexibility refers to the adjustment of warehouse space regarding the total storage area as well as the ability to vary storage utilization with respect to individual storage places [13, 14, 24, 35]. Under the term handling flexibility, the availability of different equipment, the ability to vary the amount of logistics employees or operational areas are summarized [9, 12, 13, 24]. Supply chain flexibility can be divided into external flexibility types, which are demonstrated to the customer, and internal flexibility types, which are only visible inside an operating system and used to enable the former [27, 38]. Logistics flexibility can be classified as an internal type, supporting external types like volume, product mix, new product, product customization and delivery flexibility of a supply chain. In this way, figure 1 adapts the framework of Reichhart and Holweg (2007) [38]. Transport Storing Support Processes Handling from various suppliers to a consolidation center. Depending on packaging and loading, parts are either cross-docked or stored and subsequently re-packed in disposable packing. After stowing the loading units into containers, the successive prerun of the intercontinental supply includes transportation by train to a harbor, where vessel loading is conducted. The mainrun of the overseas transport from port of departure to port of destination takes several weeks and may pass feeder ports, depending on the transportation route. After customs clearance, incoming containers are stored at a container yard. Subsequently, the after-run includes truck transportation of the containers to the plant. In case of emergency, the only alternative for the oversea supply is air freight [39, 40]. 3.2. Measuring of logistics flexibility and its adjustment The approach for tactical flexibility planning in global inbound logistics is accomplished in two steps. First, a method which supports the operationalization of logistics flexibility is derived. In this context, Barad and Sapir (2003) as well as Zhang et al. (2005) confirm that logistics flexibility is scaled based on range and response [24, 41]. The following explanations refer to Pfeiffer (2016), who builds on existing approaches in production systems and supply chains to quantify the flexibility of a distribution network. The author differentiates between metrically scaled and nominally scaled flexibility types as the internal subjects of change. The range 𝑞𝑞 ∈ 𝑄𝑄 of a flexibility potential, limited by upper and lower bounds, refers to the capacity of a metrically scaled flexibility type or to the number of alternative processes for nominally scaled flexibility types. Since a flexibility measure 𝑚𝑚 ∈ 𝑀𝑀 serves to adjust flexibility potential, the variation from 𝑞𝑞1 to 𝑞𝑞2 can be described as ∆𝑞𝑞 [14]. Figure 2 displays the model reported by Pfeiffer (2016) in a slightly modified version. Range (capacity) Upper bound II External Flexibility Effectiveness Efficiency Fig. 1. Tactical logistics flexibility in supply chains. 3. Approach for measuring and planning of overseas inbound logistics flexibility 3.1. External logistics in global inbound supply The research subject of this paper is external inbound logistics processes in international and multilevel production networks in the automotive industry. As a representative chain, the following explanations refer to globally sourced and consolidated delivered vehicle components. Directly shipped or locally sourced parts are excluded. This process generally begins after the continental overland transportation of parts set cost (c) Range Upper bound I q2 q1 Volume Product mix New product Customization Delivery Response Equipment Huamn ressources Operational area Uniformity Warehouse space Storage utilization Range Logistics Flexibility Internal Flexibility Mode Route Carrier Capacity Frequency Express delivery Supply Chain Flexibility 417 417 Lower bound I ut set ut time (t) (process) ps1b ps1a set cost (c) ps1a ut set ut time (t) Fig. 2. Metrically and nominally scaled flexibility types. Thereby, a pre-defined basic corridor, resulting from strategic 𝑚𝑚𝑚𝑚𝑚𝑚 as the lower bound and decision, can be described with 𝑞𝑞𝑝𝑝𝑝𝑝,𝑡𝑡 𝑚𝑚𝑚𝑚𝑚𝑚 as the upper bound of a process sequence 𝑝𝑝𝑝𝑝 ∈ 𝑃𝑃𝑃𝑃 within 𝑞𝑞𝑝𝑝𝑝𝑝,𝑡𝑡 a given tactical time period 𝑡𝑡 ∈ 𝑇𝑇 [14, 28, 42]. 𝑚𝑚𝑚𝑚𝑚𝑚 𝑚𝑚𝑚𝑚𝑚𝑚 𝑞𝑞𝑝𝑝𝑝𝑝,𝑡𝑡 ≤ 𝑞𝑞𝑝𝑝𝑝𝑝,𝑡𝑡 ≤ 𝑞𝑞𝑝𝑝𝑝𝑝,𝑡𝑡 (1) ∀𝑝𝑝𝑝𝑝 ∈ 𝑃𝑃𝑃𝑃; 𝑡𝑡 ∈ 𝑇𝑇 Due to the fact that implementing a flexibility measure 𝑠𝑠𝑠𝑠𝑠𝑠 for its entails corresponding expenses, setup costs 𝑐𝑐𝑝𝑝𝑝𝑝,𝑚𝑚,𝑡𝑡 𝑢𝑢𝑢𝑢 realization as well as utilization costs 𝑐𝑐𝑝𝑝𝑝𝑝,𝑚𝑚,𝑡𝑡 for its actual application need to be specified. Furthermore, the setup time 𝑢𝑢𝑢𝑢,𝑚𝑚𝑚𝑚𝑚𝑚 𝑠𝑠𝑠𝑠𝑠𝑠 as well as the minimum utilization time 𝑡𝑡𝑝𝑝𝑝𝑝,𝑚𝑚 and the 𝑡𝑡𝑝𝑝𝑝𝑝,𝑚𝑚 𝑢𝑢𝑢𝑢,𝑚𝑚𝑚𝑚𝑚𝑚 maximum utilization time 𝑡𝑡𝑝𝑝𝑝𝑝,𝑚𝑚 of a measure 𝑚𝑚 need to be described [14, 28, 42]. Sarah Fink et al. / Procedia CIRP 79 (2019) 415–420 Sarah Fink et al. / Procedia CIRP 79 (2019) 415–420 418 418 The following explanations refer to the overseas inbound supply described in chapter 3.1. In order to consider all relevant components, factors creating a shortage per process sequence on a planning level are taken into account. Therefore, these bottlenecks are either metrically scaled by their capacity, measured in form of their throughput unit, or nominally scaled by the number of alternative processes per time period. On the basis of pre-selected measures, table 1 shows that a consolidation center needs to vary storage space as well as operational space for cross-docking or packaging by renting or canceling areas. Furthermore, the availability of human resources for all tasks from goods receipt to goods issue, related to cross-docking or packing processes, need to be varied by personnel measures. Moreover, booked transportation capacities of international logistics service providers (LSP), scaled in form of the number of delivery containers (cont), need to be adjusted for the pre-, main- and after-run. Equally, the ability to vary container storage area needs to be considered at the container yard in the target market. Since these measures can be declared as capacity-related, the ability to change a service provider for the main run, as well as the ability to switch to express delivery via air freight for a defined scope of supply, can be seen as process-related [14]. Table 1. Shortage Factors per Process Sequence. 𝑚𝑚 Sequence Bottleneck Scale Unit 1 Warehousing Storage area Metrically m² 2 Cross-docking Operational area Metrically m² 3 Cross-docking Personnel capacity Metrically hours 4 Packaging Operational area Metrically m² 5 Packaging Personnel capacity Metrically hours 6 Pre-run Transport capacity Metrically Container 7 Main-run Transport capacity Metrically Container 8 Container yard Container storage area Metrically Container 9 After-run Transport capacity Metrically Container 10 Main-run Alternative carrier Nominally LSP 11 Main-run Express delivery Nominally LSP Here, it needs to be considered that the cost of a measure not only depends on the flexibility range. It also varies based on the setup and utilization time, since a short-term implementation might increase the related price. Referring to the above, in case of a flexibility increase, a measure 𝑚𝑚 contributes to a positive ∆𝑞𝑞. This is related to setup costs like contract negotiations and utilization costs like surcharge for additional cargo hold. For a flexibility decrease, a negative ∆q is aspired. In this case, setup costs occur in form of additional costs like cancellation premiums or expenses for contract adjustments. Utilization costs can be understood as saved remaining costs like remnant costs for labor, unused areas or services provided by contractual partners. In both cases, it needs to be considered that the utilization time of a measure can exceed the targeted planning period and needs to be allocated to multiple planning periods 𝑡𝑡 [14, 28, 42]. 3.3. Comparison of cost and benefits of logistics flexibility The second step of this approach is to provide a multi-period decision model, which considers the adjustment of the flexibility corridors as an investment decision for a planning period 𝑡𝑡. To determine the related expense for the adjustment of a flexibility corridor, activity-based costing is used. As described above, this includes setup cost and utilization cost for flexibility increase or decrease. In line with current literature, the use of flexibility is divided into financial and non-financial benefit. In case of an increase of flexibility (∆q>0), growth in sales figures can be expected for the financial benefit. Therefore, a pro rata revenue 𝑟𝑟 𝑏𝑏 of the contribution margin 𝐶𝐶𝐶𝐶 from non-missing sales of a number of vehicles 𝑛𝑛𝑡𝑡𝑣𝑣𝑣𝑣ℎ is assigned to logistics. Furthermore, a hypothetically assumed saving on penalties, which are usually charged in the event of an order backlog, serves to reflect avoided customer dissatisfaction due to unfulfilled orders. This is quantified based on Schütz and Tomasgard (2011) in the form of a percentage share 𝑟𝑟 𝑝𝑝 of 𝐶𝐶𝐶𝐶 amounting to 25 percent [34, 42]. In case of a flexibility decrease (∆q

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