Energy efficiency benchmarking concept for diverse ...

Dipl.-Ing. Michael Schadler Research Assistent Institute of Logistics Engineering (ITL) Faculty of Mechanical Engineering and Economic Sciences Graz University of Technology

Dipl.-Ing. Thomas Stöhr Research Assistent Institute of Logistics Engineering (ITL) Faculty of Mechanical Engineering and Economic Sciences Graz University of Technology

Dr.techn. Norbert Hafner Assistant Professor, Deputy Head Institute of Logistics Engineering (ITL) Faculty of Mechanical Engineering and Economic Sciences Graz University of Technology

Energy efficiency benchmarking concept for diverse automated storage and retrieval systems This paper deals with the energy efficiency of different types of fully automatic storage and retrieval systems. Since a direct comparison of diverse systems has never been done, a basic benchmarking procedure is proposed. This paper describes the benchmarking of three systems namely miniload-, horizontal carousel- and shuttle- systems in order to characterize parameters and specifications to derive an energy efficiency indicator. This indicator confronts the energy demand with a logistical performance. To evaluate the energy demand, the power usage of each system is measured over time while the system is operated in a pre-defined representative operating cycle. This cycle is defined by a load spectrum that consists of several operating states (full-, partial load and standby) and specific reference points that are approached by the storage and retrieval machines. Finally the paper presents a step-by-step procedure for these measurements and some limitations of the proposed benchmarking system. Keywords: energy efficiency, AS/RS, miniload, horizontal carousel, shuttle

1

INTRODUCTION

The high energy consumption of material handling systems is due to the fact that these systems operate a large amount of electrical devices. Only little knowledge about specific potentials to reduce the energy consumption in intralogistics is available. Furthermore there are few standards available to calculate or measure energy efficiency for automated storage and retrieval systems (AS/RS). The available standard methods for determining losses often meet only single components like electric drives (EN 60034) [1]. Hence, a direct comparison between different types of complex material handling and storage systems is not possible.

storage and retrieval system strongly depends on the underlying performance needs. This is often expressed in terms of the necessary transshipping performance or the storage capacity requirements. There are many different factors that influence the throughput and cycle time of AS/RS. These parameters are either design characteristics or operational policies like load shuffling, order batching, request sequencing, storage assignment or scheduling (see Figure 1). It becomes obvious that there is a big variety of AS/RS regarding the technical specifications and control strategies.

1.1 Aims and goals of this paper

In order to close the gap, a standardized procedure to measure and calculate values reflecting the energy efficiency of automated storage and retrieval systems is needed. This procedure has to be independent from the specific system design or manufacturer. The main purpose of this paper is to present a basic concept of a method to evaluate the energy efficiency of three different automated storage and retrieval systems, namely:  Miniload systems  Shuttle systems  Horizontal carousel systems 1.2 Basic prinicples of AS/RS

Main components of AS/RS are cranes or vehicles, high-bay racks and the corresponding aisles, Input/Output (I/O) points, conveyors and picking positions. The final physical configuration as well as the programming and control policy of any automated

© FME Belgrade, 2017. All rights reserved.

Figure 1. Parameters influencing throughput and cycle time of AS/RS (cp. [2])

Proceedings of the XXII International Conference MHCL’17

Although stacker cranes, horizontal carousel systems and shuttle systems essentially perform the same task, their technical nature is very heterogenous. For example there are differences regarding the rack dimensions, type of unit loads or numbers of storage compartments (see Figure 2). It is vital to define system boundaries and find a common denominator, so that a valid comparison can be made.

indicator. Such a reference value has to combine the opposing characteristics of all three AS/RS types and represent the real benefit that has been achieved by the absorbed energy. Therefore the indicator is derived from the general definition of efficiency that can be found in the EU directive 2006/32/EC [7]. This definition needs to be expanded and should be a ratio of a “general definable output of performance, service, goods or energy, depending on the application, and is set to an input of energy”. [3] 𝜂=

𝑂𝑢𝑡𝑝𝑢𝑡 𝑜𝑓 𝑝𝑒𝑟𝑓𝑜𝑟𝑚𝑎𝑛𝑐𝑒 𝐼𝑛𝑝𝑢𝑡 𝑜𝑓 𝑒𝑛𝑒𝑟𝑔𝑦

(1)

Hafner and Lottersberger [3] recommend to use a combination of several basic parameters to evaluate the output of the logistical process (“logistic performance”). 𝐸

Figure 2. Rough classification of AS/RS regarding throughput (double cycles/hour) and number of storage compartments

2

Materials and methods

2.1 Assumptions

The following assumptions are made in order to define a standardized methodology to determine the energy efficiency of automated storage and retrieval systems:  The procedure for the energy efficiency classification should be comparable to the methodolgy of conveyor systems introduced by Hafner and Lottersberger [1], [3].  The procedure and finally all measurements (working cycles, reference points etc.) should be based on or at least be similar to standardized guidelines like FEM 9.851 [4], VDI 3561 [5] or VDI 2692. [6]  The energy efficiency indicators model must be independent from any technical solution, operatorspecific control strategy or manufacturer-specific implementation.  The comparison is only valid if the storage capacity of the systems is of the same magnitude. If they are not, comparable virtual rack dimensions have to be calculated. 2.2 Energy efficiency indicator model

The benchmarking system used to quantify the energy efficiency of each system should be based on one Correspondence to: DI Michael Schadler, research assistant Institute of Logistics Engineering (ITL) Graz University of Technology Inffeldgasse 25 E, 8010 Graz E-mail: [email protected]


=

𝑊 𝐸

(2)

A specific energy demand of a process is introduced by taking the reciprocal value of the energy efficiency. 𝑒 =

1

=

𝐸

𝐸 𝑊

(3)

The “logistic performance 𝑊 ” has to represent the benefit that has been generated by the input of energy. Since the main function of AS/RS is the input and output of unit loads, the total number of storage/retrieval processes over a certain time period is a matter of particular interest. The best way to describe the benefit that is generated by the system is taking this number as a reference value. 𝑊(

)

(4)

=𝑋

The total number of unit loads is the sum of all unit loads counted in each operating state during the benchmarking process. It can also be expressed by the throughput and time intervals. 𝑋

=

𝑋 =

𝛬 ∗𝑇

The logistic performance 𝑊 ( of unit loads equals: 𝑊(

)

=𝑇 ∗

)

(5)

based on the number

𝛬 ∗𝑡

(6)

2.3 Capacity-based equivalency of AS/RS

In the following we describe a methodology, which puts miniload, horizontal carousel and shuttle system on an equal footing. This approach is suited to overcome the distinctive features of each system and is the first step to provide a comparison of the energy demand of AS/RS. The characteristic value capacity can serve as a basic reference value. The first step is to define the number of storage compartments with regard to the operators needs. This also includes the definition of the common size of the unit loads.


Since the demand-oriented capacity has to be identical for all systems, some systems have to be adopted to fit to the defined characteristic. E.g. in practice the horizontal carousel systems are the smallest fully automatic systems in such a comparison, so the number of storage compartments has to be transferred to miniload and shuttle systems. We further suggest to calculate equivalent rack dimensions for these systems. Using a reverse-engineering approach, the dimensions height and length of a virtual racking system have to be calculated (see Figure 3). Choose the desired capacity of all systems

Transfer the capacity to a single aisle rack system of a miniload system

Calculate height and length of a virtual rack by reversing the usual engineering process

Transfer the findings to a virtual shuttle system rack

standby. The total amount of time used for all recommended operating states sums up to 𝑇 = 1 ℎ.

Figure 4: Graphical visualization of the ROC

Each period is a percentage of 𝑇 and can be calculated according to: (7)

𝑇 =𝑡 ∗𝑇 Result: Three different systems are comparable based upon the logistical parameter "capacity"

Measurement and EEI calculation can be applied to virtual systems even if realworld systems deviate

Figure 3: Schematic diagram to calculate virtual rack systems in order to establish equivalency of AS/RS types

The measurement to determine the electrical power consumption is then performed using the virtual rack systems, which are mapped into the real rack systems. This has the advantage that even if the real rack systems are not equal in terms of dimensions, a comparison is still possible due to the same capacity. 2.4 Criteria for Energy Efficiency models

The different payloads within the load spectrum are defined by the relative loading 𝑚 of the nominal load 𝑀 = 25𝑘𝑔. We suggest using 90% of the unit load’s payload during full load operation and 50% of the unit load’s during partial load operation. The time period for full load operation should resemble 20% of the total time used for the measurement, while partial load operation should be 60%. Standby operation should correspond to 20% of the total time (see Table 1). These set of values for each parameter are adjustable suggestions based on comprehensive discussions with industrial partners. Since horizontal carousel systems are dynamic warehouses, we also suggest using the same coefficients for each operating state regarding the percentage of the total payload that is stored within the racking system. Table 1: Coefficients for each operating state of the ROC

The criteria needed for the energy efficiency classification process and for calculation purposes are based on the establishment of equivalency:  Dimensions of the unit loads (width, length)  Nominal payload of the unit load

 

Depending on the actual load spectrum the following operating factors have to be adopted: Load condition (portion of payload) Time interval of operating state

2.5 Specification of Representative Operating Cycles

To measure the electrical power and the energy demand respectively, a representative operation cycle (ROC) needs to be defined. The ROC represents a typical standard working cycle of an automated storage and retrieval system (see Figure 4). Per definition the ROC consists of several operating states that include the specific load spectrum that is applied to the system. The load spectrum is only defined for dual command or double cycle operation and consists of the following three phases: full load operation, partial load operation and © FME Belgrade, 2017. All rights reserved.

𝐢

Operating state

1 2

Full load Partial load Standby

3

Percentage of unit loads payload 𝒎𝒊 90% 50% 0%

Percentage of time period 𝒕𝒊 20% 60% 20%

The amount of unit loads that are stored or retrieved within the time period has to be counted. This is vital to calculate the throughput Λ . Alternatively the throughput can also be calculated by dividing the time period by the cycle time. 3

RESULTS

3.1 Definition of reference points for measurement in miniload systems

The representative operating cycle is only defined for normal single-aisle miniload systems. Curve-traversing systems are not considered.


The reference points are defined according to FEM 9.851 [4] and VDI 3561 [5]. The respective formula should be used to calculate the reference points by using the height and length of the virtual miniload rack system. If the real-world miniload rack is of different size, the ROC is performed within the dimensions of the virtual rack. If the shelf unit parameter 𝑤 ≠ 1, the integral for the expected value of the cycle time has to be calculated in order to find the positions of the reference points. With the shelf unit parameter set to w = 1 and with the geometric interpretation of the formula, the reference points with a distance of 𝑥 and 𝑦 located on the isochrones are defined according to FEM 9.851 [4] and VDI 3561 [5], as can be seen in Table 2.







The shuttle in this level takes the unit load and travels to the first position and stores the container in that storage compartment The shuttle travels to the second position ∗ L, retrieves another unit load from this storage compartments and travels back to the buffer zone The lift takes the unit load and travels back to the I/O point(s)

Table 2: Exemplary reference points for miniload systems (normal use case)

Reference Point P1 Reference Point P2

FEM 9.851 1 5𝑙 𝑃 = 2 ℎ 3 2 𝑙 3 𝑃 = 1 ℎ 5

VDI 3561 2 𝑙 3 𝑃 = 1 6ℎ 1 𝑙 6 𝑃 = 2 ℎ 3

Figure 6: Reference points of shuttle systems performing double cycles in a single level

Figure 7: Visualization of the reference points in real and virtual rack of a shuttle system Figure 5: Visualization of the reference points in real and virtual rack of a miniload system

3.3 Definition of reference points for measurement in horizontal carousel systems

3.2 Definition of reference points for measurement in shuttle systems

In a first attempt, reference points were determined by analyzing real-world live data that was acquired from database queries of customer installations. The data was provided by SSI Schäfer Automation GmbH from industrial applications. The applications are used for picking unit loads, so the horizontal carousel system also performs double cycles. The findings clearly show, that there is litte movement of the dynamic rack between storage and retrieval operations (see Figure 8).

One approach to define reference points for shuttle systems is to proceed with the derivation of reference points from scratch, using the formulas for the mean cycle times. The corresponding formulas can be found in VDI 2692 [6]. One difficulty that arises, when using the equations of this guideline, is to overcome the distinction between the separated movement of the vertical lift and the horizontal vehicle. This leads to two separate integrals that have to be considered individually. Another possibility leading to equivalent results is to use the approach and formulas introduced by Kartnig, Eder and Oser in [8], [9], [10] using the expected value of the mean cycle time. Using these approaches as basis to find the proper reference points, the reference operating cycle for shuttle systems can be defined in the following way (see Figure 6 and Figure 7):  The lift travels to the level

Figure 8: Relative frequency of travelled distance between two double cycles (x-coordinate)



Therefore we believe that it is suitable to define the reference points according to the guideline VDI 4480-3 [11]. In every horizontal carousel system the number of storage compartments is defined in each coordinate x, y and z with the maximum values n, m, k. Each I/O point of the horizontal carousel system is allocated a fixed group of reference locations. The points of origin 𝑃 are defined as the nearest storage compartments from the I/O point(s). According to the guideline VDI 4480-3 [11], the first reference point 𝑅 is derived from 𝑃 as follows:  The x-coordinate of 𝑃 is simultaneously the xcoordinate of 𝑅  If the y-coordinate of 𝑃 is equal to 1, then the ycoordinate of 𝑅 is equal to m  If the y-coordinate of 𝑃 is > 1, then the ycoordinate of 𝑅 is less than the y-coordinate of 𝑃 by 1  The z-coordinate of 𝑃 is always equal to 1, the zcoordinate of 𝑅 is thus always equal to k All further reference points can now be found by proceeding from 𝑅 , increasing the x-coordinate by 1 and decreasing the y-coordinate by 1 (see Figure 9).

boundaries need to be defined in such a way, that the shuttle vehicle is included as there are many different types of energy supply for the shuttle’s drivetrain (eg. battery, capacitor, conductor rail).

Figure 9: Example of a horizontal carousel system and it’s reference points [11]

Figure 11: System boundaries of each AS/RS system

3.4 Power measurement while operating AS/RS in specified ROC

In order to conduct proper power measurements to determine the electrical energy demand, the system boundaries of each system have to be defined. The system boundaries should include the complete construction ranging from drive trains, regulator control elements to control systems, and thus contain everything necessary to store a unit load. This enables the direct comparison of input and output of the system (see Figure 10).

Input (energy)

AS/RS

Output (logistic performance)

Figure 10: Considering the system as a black box (cp. [12])

Figure 11 shows the system boundaries of each AS/RS system, which are used for determining and measuring the power demand. The measurement includes all electric appliances of the AS/RS system. For shuttle systems, the system © FME Belgrade, 2017. All rights reserved.

3.5 Calculation of the energy demand and energy efficiency indicator

The specific energy demand is the starting point of the following considerations. The power consumption 𝑃 that is measured during each phase of the representative operating cycle is multiplied by the corresponding portion of time 𝑇 . All phases summed up result in the total energy demand 𝐸 of the ROC. This equals the energy that is necessary to store and retrieve the unit loads. 𝐸 =𝑇 ∗

𝑃 ∗𝑡

(8)

With the formula to calculate the logistic performance 𝑊 ( ) (see (6)), we can calculate the specific energy demand. The indicator is expressed in SI-units (Ws/unit load). ∑ 𝑃 ∗𝑡 𝑒 = (9) ∑ 𝛬 ∗𝑡


4

CONCLUSION

This study presents a new possibility to compare and evaluate the energy efficiency of different types of fully automated storage and retrieval systems that overcomes the diverse nature of miniload systems, horizontal carousel systems and shuttle systems. Figure 12 provides a short but vital step-by-step guide to perform the benchmarking. The new approach has some limitations. The comparison is only valid if the storage capacity of the systems is of the same magnitude. The methodology has already been verified for miniload systems within the research project „Energieeffizienz komplexer Materialflusssysteme“ (en: energy-efficiency of complex material flow systems, FFG project number 848452) funded by the Austrian Research Promotion Agency. All other systems are to be tested and analyzed in the near future.

𝑇

Total amount of time [s]

𝑃

Measured power demand in a specific time period

𝑒

Specific energy demand

𝑃

Point(s) of origin

𝑃 ,𝑃 𝑅 5

[1]

[2]

[3]

[4] [5] [6] [7] [8] Figure 12: Overview of the complete benchmarking procedure

[9]

NOMENCLATURE

𝐸

Energy efficiency [10]

𝐸

Energy input

𝑊

Logistic performance double cycle

𝐷𝐶

Double cycle

[11]

𝑋

Total amount of unit loads

[12]

𝑋

Amount of unit loads in a specific time period

𝛬

Throughput in a specific time period

𝑡

Specific time period in [%]

𝑇

Specific time period in [s]


Reference points (VDI 3510, VDI 2692, FEM 9.851) First reference point (VDI 4480-3)

REFERENCES

N. Hafner and F. Lottersberger, Energy Efficiency in Material Flow Systems: effMFS, in XX International Conference on "Material Handling, Constructions and Logistics", MHCL '12, 3 - 5 October 2012, University of Belgrade, Faculty of Mechanical Engineering, S. Bošnjak (Ed.), Belgrade, 2012. M. Schumann, Zur Bestimmung der Umschlagleistung von Hochregallagern unter besonderer Berücksichtigung der Lagerorganisation, Dissertation, Technische Universität, Chemnitz, 2007. F. Lottersberger, N. Hafner, and D. Jodin, Efficiency Indicators for Benchmark and Improvement of Energy Efficiency on Automated Material Flow Systems, in Proceedings in Manufacturing Systems, G. Constantin and A. Ghionea (Eds.), 2013. FEM 9.851: Leistungsnachweis für Regalbediengeräte: Spielzeiten, VDMA Fachverb. Fördertechn, Frankfurt, 2003. 3561-1, Richtlinie: Testspiel zum Leistungsvergleich und zur Abnahme von Regalförderzeugen, Beuth, Berlin [u.a.], 1973. 2692, Richtlinie: Shuttle-Systeme für Kleinbehälterlagerung, Beuth, Berlin, 2014. Endenergieeffizienz und Energiedienstleistungen: 2006/32/EG, 2006. G. Kartnig and J. Oser, Throughput analysis of S/R shuttle systems, In-ternational Material Handling Rese-arch Colloquium 2014, 2014. M. Eder and G. Kartnig, Throughput analysis of S/R shuttle systems and ideal geometry for high performance, FME Transaction, vol. 44, no. 2, 2016, pp. 174–179. M. Eder and G. Kartnig, Durchsatzoptimierung von Shuttle-Systemen mithilfe eines analytischen Berechnungsmodells, 2016. 4480-3, Richtlinie: Durchsatz von automatischen Umlauflagern, Beuth, Berlin, 1999. T. Schilling et al.: Analyse und Quantifizierung der Umweltaspekte von Fördermitteln in der Intralogistik: [Forschungsbericht], Teil 2, available at: http://www.femeur.com/data/File/Teil_2_Forschungsbericht_Um weltauswirkungen_Intralogistik.pdf,
