Method for changing at least one production site in a network of production sites

Abstract

Method for changing at least one production site (14, 16, 18, 20) in a network (22) comprising a plurality of production sites (14, 16, 18, 20), characterized in that an actual state (12, 24) of the respective production site (14, 16, 18, 20) is detected on the basis of at least one predetermined criterion (26, 28, 30, 32, 34, 36) that can be quantified by means of a computing device, wherein for the at least one criterion (26, 28, 30, 32, 34, 36) a potential (42) of the respective production site (14, 16, 18, 20) with regard to changing the respective production site (14, 16, 18, 20) is determined, wherein taking into account the potentials (42) of all production sites (14, 16, 18, 20) a target state (44, 46, 48, 50) of the respective production site (14, 16, 18, 20) is specified, wherein by changing at least one of the production sites (14, 16, 18, 20) with regard to the at least one criterion (26, 28, 30, 32,34, 36) the target state (44, 46, 48, 50) of the respective production location (14, 16, 18, 20) is realized, and wherein by changing the at least one production location (14, 16, 18, 20) a target value for the at least one criterion (26, 28, 30, 32, 34, 36) is achieved.

Description

[0001] The invention relates to a method for changing at least one production site in a network comprising a plurality of production sites.

[0002] Currently, the planning of factory structures or production sites, for example in the automotive industry, is one-dimensional and based on fixed planning premises from the individual vehicle projects. For example, the production site is designed so that a new product in the form of a new vehicle model can be produced at the site throughout its lifetime. Furthermore, long-term sales planning over the lifetime period is taken into account. However, this approach does not, or only to a limited extent, maintain flexibility reserves and capacity reserves. The factory structures or production sites therefore often have only a limited degree of adaptability. Furthermore, factory structures are now planned in isolation at the individual locations, so that synergies and potential within a plant network, i.e. a network of several production sites, are hardly taken into account.

[0003] In contrast, DE 10 2010 041 251 A1 describes a method for planning a production network with a real geographical extent, in which various proposals for the finished network are evaluated. Evaluation criteria that depend on the respective production location can be incorporated. The primary optimization goals of the evaluation in this method are aspects of cost-effectiveness, the number of units to be produced, and criteria for the required product quality.

[0004] A disadvantage of such approaches is that changing conditions, for example with regard to products to be manufactured, product variants, unit quantities, and technical characteristics of the products, often lead to significant planning effort when adapting a structure or production site. This is accompanied by high additional investments and increasing structural complexity. When viewed in isolation, it can also happen that suboptimal changes are made at individual production sites, while an overall optimum is not achieved within the network of production sites.

[0005] The object of the present invention is therefore to create a method of the type mentioned at the outset, by means of which it is possible to react more effectively to changing framework conditions.

[0006] This object is achieved by a method having the features of patent claim 1. Advantageous embodiments with expedient further developments of the invention are specified in the dependent patent claims.

[0007] In the method according to the invention for changing at least one production site in a network comprising a plurality of production sites, the actual status of the respective production site is first recorded using at least one predetermined criterion that can be quantified by a computing device. The respective production site can be designed, in particular, for the manufacture of motor vehicles.

[0008] In a next step, the potential of the respective production site is determined for the at least one criterion with regard to changing the respective production site. Taking into account the potential of all production sites, a target state for the respective production site is then specified. By changing at least one of the production sites with regard to the at least one criterion, the target state of the respective production site is realized. By changing at least one of the production sites with regard to the at least one criterion, a target value for the at least one criterion is achieved.

[0009] By using at least one predetermined criterion, which is quantified by the computing device, the different production sites are made comparable with regard to their actual status. In addition, at least one criterion is used to determine the potential of each production site. This determines what contribution each production site can make to enable the network of production sites to respond more effectively to changing conditions. Because the potential of all production sites is taken into account when specifying the target status of each production site, it may happen that potentially possible changes to a production site are omitted or not made. Potential is therefore preferably exploited at a production site only to the extent that it seems sensible and is necessary.Nevertheless, the network of production sites or plants strives for maximum flexibility and achieves this by making appropriate changes to at least one of the production sites. This allows for a better response to changing conditions.

[0010] By implementing the target state of each production site, adaptable factory structures or production sites are created. This creates robustness against various future scenarios. Such future scenarios can be addressed through rapid and low-cost adaptation of the structures or production sites. Furthermore, the approach of determining the potential of all production sites rather than examining it singly at the site level leads to a holistic utilization of synergies within the network. This allows each production site to focus on its strengths. Weaknesses can be specifically compensated for by other production sites.

[0011] By taking a cross-site approach, an overall optimum can be achieved within the plant network, rather than local optima at each plant or production site. This takes into account the individual strengths and potential of each production site. However, maximum flexibility at each production site does not need to be achieved at any cost.

[0012] By specifying the target state, a binding planning specification is created for each production site, which must be observed by trade planners and / or structural planners to account for flexibility reserves. This prevents unnecessary flexibility or insufficient flexibility with regard to the products, variants, quantities, and technologies that can be manufactured at the respective production site. Overall, this reduces and optimizes the planning effort and the investments associated with changing at least one site. Furthermore, maximum transparency of the production sites is created.

[0013] When specifying the target state of the respective production site, it is preferably considered whether the target state can be more easily achieved at a first of the production sites with regard to the at least one criterion than at at least one other of the production sites. This allows resources to be used particularly efficiently to change the production sites.

[0014] When assessing the feasibility of the target state at the respective production site, the availability of space at the production site and / or in the vicinity of the production site can be taken into account. Additionally or alternatively, the adaptability of at least one facility at the production site can be considered when assessing feasibility. This allows for consideration of the degree of adaptability that can actually be achieved given framework conditions such as space availability. Furthermore, consideration can be given to the degree of adaptability that makes economic sense. The technical conditions of the at least one facility at the production site play a role here.

[0015] Preferably, the target state of each production site is specified in such a way that differences in the changeability of the respective facilities at the production site are reduced. The facilities at the production site are run through sequentially for the production of a product that can be manufactured at the production site.

[0016] If the production site is designed to manufacture motor vehicles, the facilities could, for example, be individual trades such as body shop, paint shop (i.e., a shop for painting the body), and subsequent assembly. If the adaptability of one such facility is comparatively high, but (still) comparatively low at another, it is preferable to ensure that a similar level of flexibility or adaptability is achieved across all trades at the respective production site. This prevents, for example, the low flexibility of one individual trade from limiting the adaptability of the entire production site.

[0017] Preferably, a simulation model is used to determine the potential of all production sites. The simulation model includes elements designed to represent a production site.

[0018] By using such elements, designed like a modular kit, a real production run or a simple concept for future production can be quickly and easily modeled. Furthermore, modifications can be implemented quickly and easily to enable more informed conclusions.

[0019] The simulation model can also be used to obtain at least one of the criteria describing the current state of the respective production site in a form that can be quantified, particularly by means of the computer. This allows for the fact that certain criteria describing the current state of the respective production site cannot always be easily provided solely based on concrete information that can be provided by experts available at the respective production site.

[0020] Control variables of the simulation model preferably include different products to be manufactured at the respective production site, in particular different series or models of a motor vehicle, and / or a number of variants of the respective product, for example, different body versions of a model. Furthermore, the control variables of the simulation model can include a producible number of units of a product to be manufactured at the respective production site per unit of time and / or a technical characteristic of the product to be manufactured at the respective production site.

[0021] By changing such control variables, plausible future scenarios can be created very quickly and easily, indicating a possible future design of the production site. The modified production sites resulting from each scenario can then be subjected to a robustness test. This check determines whether the modified production site allows adaptation to the changed framework conditions underlying that scenario, even if another scenario occurs. This allows for a quick and easy determination of which scenario can be implemented with reasonable effort.

[0022] Preferably, the current status of the respective production site is recorded based on a plurality of predetermined criteria that can be quantified by the computer. These criteria allow the current changeability of the respective production site to be assessed. Based on these criteria, the potential of the respective production site with regard to change is then determined. By considering a plurality of quantifiable criteria, the current status of the production site can be recorded particularly accurately and realistically.

[0023] The predetermined criteria may include at least two criteria from a group including volume flexibility, capacity expansion capability, variant capacity reserve, model mix flexibility, variant flexibility, and shift flexibility. The at least two criteria are considered for the respective production site.

[0024] Volume flexibility describes the ability to adjust production volume at short notice. Capacity expansion capability, on the other hand, describes the ability to adjust production volume through specific investments within a predetermined response time.

[0025] The variant capacity reserve describes the ability to adjust the respective shares of the total production volume of the production site for models and derivatives of a motor vehicle. Model mix flexibility describes the ability to implement different production programs at the same production site, i.e., to produce variants of a motor vehicle model in different sequences, for example.

[0026] Variant flexibility describes the ability to produce models and derivatives that are in demand in a local market at the production site. Shift flexibility describes the ability to shift a production volume between at least two production lines.

[0027] By considering at least two of these criteria, and in particular all of them, a reliable, robust statement can be made, particularly with regard to the short- to medium-term adaptability of the respective production site. This short- to medium-term adaptability preferably refers to a period of up to seven years and thus to the current model life cycle of a motor vehicle.

[0028] Preferably, at least one key figure is calculated by the computing device to quantify the at least one predetermined criterion. Thus, by comparing the key figures assigned to the respective criteria, the actual states of different production sites can be compared particularly easily.

[0029] The invention also includes combinations of the described embodiments.

[0030] Exemplary embodiments of the invention are described below. Shown are: Fig. 1 schematically shows curves describing the actual state of two production sites with regard to various predetermined criteria indicating a capacity for change; Fig. 2 schematically the determination of a potential and a target state for the respective production site, taking into account the criteria indicating the ability to change; and Fig. 3 the implementation of the target states of different production sites with the aim of maintaining maximum change capability within the network of production sites.

[0031] The exemplary embodiments explained below are preferred embodiments of the invention. In the exemplary embodiments, the described components of the embodiments each represent individual features of the invention that can be considered independently of one another, each of which also develops the invention independently of one another. Therefore, the disclosure is intended to encompass combinations of the features of the embodiments other than those shown. Furthermore, the described embodiments can also be supplemented by further features of the invention already described.

[0032] In the figures, functionally identical elements are provided with the same reference numerals.

[0033] In order to create adaptable factory structures or production sites, the current status of each production site is first recorded. This will be illustrated using the example of production sites dedicated to the manufacture of motor vehicles. However, the approach can be transferred to other manufacturing industries in order to record the respective current status of the production sites and determine an optimal operating point, particularly from an economic perspective.

[0034] In Fig. 1, a first curve 12 shown in a polygonal network 10 illustrates the actual state of a first production site 14, which in Fig. 3 is shown schematically by a box. Further production sites 16, 18, 20 are in Fig. 3 is illustrated schematically by further similar boxes. In Fig. 3 also shows a network 22, which includes all of the production sites 14, 16, 18, 20 under consideration. The number of production sites 14, 16, 18, 20 shown here is merely exemplary to illustrate the procedure for converting or modifying the individual production sites 14, 16, 18, 20.

[0035] In Fig. 1, another curve 24 shows the actual state of another production site, for example the one in Fig. 3. In this case, more adaptable factory structures or production sites 14, 16, 18, and 20 are to be created or developed by moving away from a rigid planning scenario toward multidimensional planning, considering various future scenarios. The short- to medium-term adaptability of a site or structure describes the ability to respond to changes, for example, with regard to unit numbers or fluctuations in the model mix.

[0036] Long-term adaptability, on the other hand, takes into account future scope for adapting production sites 14, 16, 18, 20 with longer response times and defined investment requirements. Such long-term changes can be triggered, for example, by the integration of new products to be manufactured at the respective production sites 14, 16, 18, 20 or the construction of additional, preferably use-neutral and expandable buildings.

[0037] To determine an appropriate level of change capability for each production site 14, 16, 18, 20, it is important to consider the individual requirements and strengths of each production site 14, 16, 18, 20. The goal should therefore not be to prepare each site for all future eventualities, but rather to identify the optimal operating point for each production site 14, 16, 18, 20. The interaction of all production sites 14, 16, 18, 20 enables maximum change capability within the network 22. This approach can also be scaled up to an entire corporate structure or brand structure.

[0038] Key points of the Fig. The polygonal network 10 shown in Figure 1 illustrates dimensions of changeability or respective criteria that describe the changeability of the respective production site 14, 16, 18, 20. Each of these criteria can be quantified mathematically using a key figure obtainable by a computer. With regard to the short-term to medium-term changeability of the respective production site 14, 16, 18, 20, for targeted adaptation with short to medium reaction times, criteria such as volume flexibility 26, capacity expansion capability 28, variant capacity reserve 30, model mix flexibility 32, variant flexibility 34, and shift flexibility 36 can be considered for determining the current state. Fig. 1, points 38 and 40 indicate the extent to which these flexibilities are currently achieved for the respective production sites 14, 16, 18, and 20. Points 38 and 40 are located on respective, equally long lines leading from a center point of network 10 to a respective corner point of network 10. At each corner point, the respective flexibility is 100 percent achieved.

[0039] The respective points 38 of curve 12 and the respective points 40 of curve 24 therefore give the key figure, for example in percent, and thus the ability to change with regard to the respective Fig. 1 considered criterion again.

[0040] For example, using shift flexibility 36 as an example, we will explain below how the corresponding key figure, which can be specified in particular as a percentage, can be determined. Shift flexibility 36 is a measure of the ability to shift, i.e., shift, a production volume of derivatives of a model between individual production lines at production locations 14, 16, 18, 20. Shift flexibility 36 is calculated, for example, by taking the number of derivatives that can be produced on more than one production line of a particular trade, divided by the total number of derivatives that can be produced in the particular trade. This results in a fraction for each trade. The sum of these fractions is then divided by the total number of trades at the respective production location 14, 16, 18, 20 to obtain shift flexibility 36 for the respective production location 14, 16, 18, 20 as a percentage.

[0041] For example, the shift flexibility 36, which can be specified by one of the points 38 of curve 12, is to be calculated for production site 14, which has three trades, namely the body shop, the paint shop, and the assembly shop. Seven derivatives can be manufactured in the body shop, whereby one of the seven derivatives can be manufactured on two different production lines of the body shop. For the body shop, this results in a break with the value at production site 14. 17.

[0042] Seven derivatives can also be manufactured in the paint shop, with three derivatives being produced on two different production lines of the paint shop. For the paint shop, this results in a break with the value at production site 14. 37. And in the assembly trade, seven derivatives can also be manufactured, whereby two of the seven derivatives can be manufactured on two different production lines of the assembly trade. For the assembly trade, this results in a break with the value at production site 14. 27.

[0043] If you divide the sum of these fractions 17, 37 and 27 by the number of trades at the production site 14, i.e. by 3, the value for shift flexibility 36 is 28.6 percent.

[0044] In this way, the different production sites 14, 16, 18, and 20 can be evaluated and compared with regard to the facets of change capacity specified by the criteria. Curves 12 and 24, which each indicate the current status of one of the production sites 14, 16, 18, and 20, can differ considerably for plants built from scratch from the actual curves for existing sites with rigid and historically evolved structures. This is because different conditions exist with regard to change capacity.

[0045] In order to calculate the key figures that quantitatively describe the respective criteria, particularly those indicating short- to medium-term flexibility, data available from experts such as planners of the respective trades at production sites 14, 16, 18, 20 can be used. Furthermore, such data can be obtained from experts who determine the production program to be executed at the respective production sites 14, 16, 18, 20. The production program is determined depending on demand. The planners of the trades, in turn, can use the data they provide to specify the basic design of the respective production sites 14, 16, 18, 20.

[0046] However, some of the criteria described by the key figures cannot be described with sufficient precision based solely on the data provided by these experts. This applies, for example, to the criterion of variant capacity reserve 30. To determine the variant capacity reserve 30, for example, a simulation model can be used in which restrictions are embedded.

[0047] The actual state of the respective production site 14, 16, 18, 20, which can be described by the respective curve 12, 24, indicates the status quo of a respective site with regard to its ability to change, but not the potential of the respective production site 14, 16, 18, 20. In order to define a target state of the respective production site 14, 16, 18, 20, it is first necessary to determine the potential with regard to the ability to change of the production site 14, 16, 18, 20 for each production site 14, 16, 18, 20. This should be done using Fig. 2 can be illustrated.

[0048] In the Fig. 2 In the network 10 shown on the left, curve 12 indicates the actual state of one of the production sites 14, 16, 18, 20. In the polygonal network 10, the respective corners again indicate a value of 100 percent for the volume flexibility 26, the capacity expansion capability 28, the variant capacity reserve 30, the model mix flexibility 32, the variant flexibility 34 and the shift flexibility 36. After determining the actual state, which can be described by curve 12, the potential of the respective production site 14, 16, 18, 20 is determined, for example by creating a potential curve 42, which is shown in the same, in this case hexagonal network 10 in the middle representation in Fig. 2. To determine the potential curve 42, expert data can be entered into a simulation model, which includes, for example, possible measures, the costs associated with these measures, and the areas required for them.

[0049] When determining potential curve 42, the degree of changeability that can actually be achieved due to framework conditions such as space availability must be considered. Furthermore, the question of what degree of changeability is economically viable must be addressed. To answer these questions, control variables of the simulation model can be changed, which can include, for example, the products to be manufactured, their variants or derivatives, the number of units to be produced per unit of time, and the respective technical properties of the products to be manufactured at the respective production sites 14, 16, 18, 20.

[0050] By changing these control variables, different, plausible future scenarios are created using the simulation model. For each of these scenarios, a specific factory structure or a possible modified production site 14, 16, 18, 20 is then developed. This takes into account the basic layout, material flow, manufacturing concept, and space concept of the respective production site 14, 16, 18, 20.

[0051] In the next step, a robustness check is preferably performed for each resulting factory structure to determine whether this factory structure is effective or practical if a different scenario occurs. In particular, this considers whether the possible factory structure or the possible modified production site 14, 16, 18, 20 can fundamentally be adapted to alternative conditions and what time and financial effort would be required to achieve this. To assess this, the simulation model is used in addition to analytical approaches that include key performance indicators.

[0052] Subsequently, a target state must be selected for each production site 14, 16, 18, 20 and established as the future target image for site structure development. A corresponding target curve 44, which is represented in the hexagonal grid 10, is shown in the Fig. 2 right diagram. However, before determining the respective target curve 44, the respective potential curve 42 is determined for each of the production sites 14, 16, 18, 20, which is shown in the Fig. 2 middle illustration for one of the production sites 14, 16, 18, 20 is shown as an example.

[0053] In Fig. 3 illustrates, for example, the production site 14 in the hexagonal network 10 according to Fig. 2, the target curve 44 illustrates the target state of this production site 14. In an analogous manner, further target curves 46, 48, 50 illustrate the target states of the other production sites 16, 18, 20. However, these target curves 44, 46, 48, 50 are only created when the potential curves have been determined for all production sites 14, 16, 18, 20, of which Fig. 2 the potential curve 42 for one of the production sites 14, 16, 18, 20 is shown as an example.

[0054] The target curves 44, 46, 48, 50 specified for the respective production site 14, 16, 18, 20 offer an optimum of change capacity, space requirements, and investment at the respective production site 14, 16, 18, 20. Any deficits in partial aspects of change capacity are compensated for by other production sites 14, 16, 18, 20 in the network 22. This is done when more favorable conditions exist at this production site 14, 16, 18, 20 with regard to this partial aspect. Overall, this results in maximum change capacity being created in the network 22 of the production sites 14, 16, 18, 20. This maximum change capacity is defined in Fig. 3 is schematically illustrated by a curve 52 resulting from the target curves 44, 46, 48, 50, which is assigned to the composite 22.

[0055] Overall, the examples demonstrate how the invention can be used to implement a procedure for planning adaptable factory structures or adaptable production sites 14, 16, 18, 20 within a network 22 or a network of plants. Thus, an optimal alignment of all production sites 14, 16, 18, 20 of a production network with regard to their adaptability is achievable.

Claims

[1] Method for changing at least one production site (14, 16, 18, 20) in a network (22) comprising a plurality of production sites (14, 16, 18, 20), characterized bythat an actual state (12, 24) of the respective production location (14, 16, 18, 20) is recorded on the basis of at least one predetermined criterion (26, 28, 30, 32, 34, 36) that can be quantified by means of a computing device, wherein for the at least one criterion (26, 28, 30, 32, 34, 36) a potential (42) of the respective production location (14, 16, 18, 20) with regard to changing the respective production location (14, 16, 18, 20) is determined, wherein taking into account the potentials (42) of all production locations (14, 16, 18, 20), a target state (44, 46, 48, 50) of the respective production location (14, 16, 18, 20), wherein by changing at least one of the production sites (14, 16, 18, 20) with regard to the at least one criterion (26, 28, 30, 32, 34, 36) the target state (44, 46, 48, 50) of the respective production site (14, 16, 18, 20) is realized, and wherein by changing the at least one production site (14, 16, 18,20) a target value for at least one criterion (26, 28, 30, 32, 34, 36) is achieved., [2] Method according to claim 1, characterized by that when specifying the target state (44, 46, 48, 50) of the respective production location (14, 16, 18, 20), it is taken into account whether the target state (44, 46, 48, 50) is easier to realize at a first of the production locations (14, 16, 18, 20) with regard to the at least one criterion (26, 28, 30, 32, 34, 36) than at at least one further of the production locations (14, 16, 18, 20). [3] Method according to one of the preceding claims, characterized by that when assessing the feasibility of the target state (44, 46, 48, 50) at the respective production site (14, 16, 18, 20) - availability of space at the production site (14, 16, 18, 20) and / or in the vicinity of the production site (14, 16, 18, 20) and / or - the ability of at least one facility of the production site (14, 16, 18, 20) to change is taken into account. [4] Method according to claim 3, characterized by that the target state (44, 46, 48, 50) of the respective production site (14, 16, 18, 20) is specified in such a way that differences in the changeability of respective facilities of the production site (14, 16, 18, 20) are reduced, which are successively run through for the manufacture of a product that can be manufactured at the production site (14, 16, 18, 20). [5] Method according to one of the preceding claims, characterized by that a simulation model is used to determine the potentials (42) of all production sites (14, 16, 18, 20), which has elements designed to represent a production site (14, 16, 18, 20). [6] Method according to claim 5, characterized by that control variables of the simulation model - different products to be manufactured at the respective production site (14, 16, 18, 20) and / or a number of variants of the respective product and / or - a number of units that can be produced per unit of time and / or a technical characteristic of a product to be manufactured at the respective production site (14, 16, 18, 20). [7] Method according to one of the preceding claims, characterized by that the actual state (12, 24) of the respective production location (14, 16, 18, 20) is recorded on the basis of a plurality of predetermined criteria (26, 28, 30, 32, 34, 36) that can be quantified by means of the computing device, wherein the potential (42) of the respective production location (14, 16, 18, 20) with regard to changing the respective production location (14, 16, 18, 20) is subsequently determined for these criteria (26, 28, 30, 32, 34, 36). [8] Method according to claim 7, characterized byin that the predetermined criteria (26, 28, 30, 32, 34, 36) comprise at least two criteria (26, 28, 30, 32, 34, 36) from a group which includes a volume flexibility (26), a capacity expansion capability (28), a variant capacity reserve (30), a model mix flexibility (32), a variant flexibility (34) and a shift flexibility (36). [9] Method according to one of the preceding claims, characterized by that at least one key figure is calculated by means of the computing device in order to quantify the at least one predetermined criterion (26, 28, 30, 32, 34, 36).

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