New modeling formalism for the energy simulation of conveyor systems
Introduction
A conveyor system is a material handling equipment that addresses the movement, storage, and management of all related materials including raw materials, parts, goods, and products for processes (e.g., cleaning, preparation, manufacturing, packaging, distribution, consumption, and disposal). A conveyor system provides durable and reliable automated logistics services to the facilities for warehouse, mining, and production systems (Pang & Lodewijks, 2005). To succeed in those logistic operations, a conveyor system must be capable to react appropriately to various demands (Hsieh, Chang, & Chang, 2007). Therefore, in the logistics-planning phase, a conveyor system must be designed flexibly and efficiently to prevent loss by reconfiguration after installation (Chin et al., 2011, Zhao and Lin, 2011).
For the construction of a conveyor system, engineers design the layout of the conveyor network (Müller-Boyaci and Wenzel, 2016) and determine the type, size, power, and speed of the conveyor units based on their physical features (e.g., weight and size) of the target materials and the performance goals (e.g., lead time) (Luo, Huang, & Zhang, 2015). After installation, a conveyor system has an energy cost, which is a considerable portion of its operation cost. Thus, reducing the energy consumption of a conveyor system can save operation cost (Dong & Luo, 2011). Furthermore, reduced energy consumption contributes to the sustainable operation of a target system by preparing for future energy cost increases by regulations, such as carbon dioxide reduction for green industry (Paul et al., 2014, Rohrmus et al., 2015).
Although the energy consumption of a conveyor system must be considered as one of the KPIs (Key performance indicators) during the design phase (Sáenz, Celik, Asfour, & Son, 2012), existing research has focused mainly on smooth material flow controls. Proposed approaches in the existing research use simulation and linear programming-based numerical methods to estimate and optimize KPIs, such as average travel time, time-delay, bottlenecks (Johnstone, Creighton, & Nahavandi, 2015), flow/feed rate capacities (Göttlich, Hoher, Schindler, Schleper, & Verl, 2014), work-in-process levels (Matsui, 2005), and the expected waiting time and buffer size of each station (Bozer & Hsieh, 2004). However, various plans using the advanced operation control techniques of conveyor systems by information technologies can be developed in the design phase (Lev, Mayer, Wohlmuthová, & Prošek, 2013), and numerical methods are limitedly usable to describe unit entity performance and simple material flows and difficult to represent the systematic performance of complex plans (Herazo-Padilla et al., 2015, Ho and Lin, 2017). Simulation methods can describe rapidly the consequence of various KPIs of a system plan in many operation scenarios by the construction and modification of a virtual conveyor system (Ham and Park, 2014, Klaas et al., 2016, Wang et al., 2016). Therefore, the energy efficiency of a conveyor system can be predicted using simulations similar to other KPIs (Alyamani, Damgacioglu, Celik, Asfour, & Feiock, 2016).
Previous research on modeling conveyor systems pertains to the improvement of mechanical systems for driving, such as rollers, belts, chains, or motors (Alspaugh, 2003), and to obtain optimal parameters for electric power, speed, and feed rate under the target operational conditions (Zhang & Xia, 2011). This research focuses on conveyor systems for enhancing the energy efficiency for material handling systems with continuous operations and constant speed. In terms of time-of-use, conveyor systems for the irregular transportation of relatively small and light materials can be modeled as discrete operation systems that control each conveyor zone by entering an idle state, if it is irrelevant with material transportation (Zhang & Xia, 2010). These technology-based conveyors can reduce energy consumption (Poon et al., 2011) in conditions where a conveyor unit has sufficient time for a turn on/off operation and requires less energy to shut down and restart than the total idle energy consumption. Conveyor systems in many warehouses and assembly lines have adopted the discrete conveyors for energy efficiency, and the energy consumption of those conveyor systems relies more on the system operation control than on each conveyor performance. Thus, the simulation method is useful to predict the performance of complex conveyor systems including energy efficiency (Ko & Park, 2014), and must represent material flows in conveyor streams to achieve the objective of simulations.
However, existing modeling approaches for conveyor simulation are devised to describe system states without considering material handling (Castro, Kofman, & Wainer, 2010). The objective of this research is to model a conveyor system to simulate material-flows in the model to predict operation performance including energy consumption. For conveyor system simulation, the multiple material transportation and conveyor operation switching (on and off) by material load states must be modeled. To meet the requirements, we propose a new modeling formalism by extending the discrete event system specification (DEVS) formalism (Zeigler, Praehofer, & Kim, 2000), which is called ‘E-DEVS’ (abbreviation of the extended DEVS) in this paper. This paper constructs simulation entities by modeling the operations of each component in a conveyor system using the proposed E-DEVS formalism. Each simulation entity has an energy model that determines energy consumption states in the operation states of a simulation entity. In this research, the energy consumption states and rates are defined for discrete-material flows by the reverse engineering that is the abstraction of energy consumption data acquired from real conveyor operations (Choi & Xirouchakis, 2014). The main objective of the research is to propose modeling methodology to represent components in conveyor systems by E-DEVS-based simulation entities and to construct a conveyor system model using the simulation entities. The conveyor system model can describe energy consumption results by simulations in various network designs and logistic scenarios, and this paper describes the construction and simulation process of a conveyor system model as an example implementation.
The remainder of this paper is organized as follows. Section 2 provides the technical approach used in this research and explains E-DEVS formalism in detail. Section 3 describes the E-DEVS-based modeling methodology for conveyor systems. The implemented models and simulation results are illustrated as an example in Section 4. Finally, the conclusions are provided in Section 5.
Section snippets
Description of candidate conveyors
This research categorizes candidate conveyors as two operation types, continuous and discrete conveyors. The continuous operation type is used in conventional conveyors in many existing facilities, and it provides stable transportation for a wide range of materials in size and weight. However, energy can be wasted by operating regardless of whether materials are loaded. This conveyor type has been implemented with various device types including belt, roller, and chain conveyors. Fig. 1 depicts
E-DEVS-based conveyor system modeling
To construct a conveyor simulation system, this research defines the following simulation entities: source, sink, junction, continuous conveyor (conveyor_C), and discrete conveyor (conveyor_D); and a material entity: part. Each simulation entity has input and output ports and a process. The output port of a simulation entity is connected to the input ports of other entities. A material entity that describes the material characteristics by their attributes is generated in a source entity and
Implementation
The software application that implements the proposed methodology has been developed using the C# language and DEVSIM++ (Kim, 1994) for the simulation engine and conveyor models, and the Syncfusion® library for the graphical user-interface. To validate the modeling formalism and reverse energy models of this paper, we constructed a demo conveyor system and had experiments with measurement devices in controlled operation conditions as Fig. 16. It is difficult to measure the energy consumption of
Concluding remarks
This paper proposed the E-DEVS modeling methodology for the construction and simulation of conveyor system models. The proposed E-DEVS formalism was able to represent the conveyor operational characteristics that describe the conditional operations by material load states and the concurrent operations for multiple materials transportation. The proposed methodology describes the operations of components in conveyor systems as operation states based on the E-DEVS formalism, and assigns each
Acknowledgements
This work was supported by the Technology Innovation Program (20002772, Development of the smart manufacturing collaboration system for the innovation of pipe and steel outfit and block logistics in the shipbuilding and marine) funded by the Ministry of Trade, Industry & Energy (MOTIE, Korea). Also, the research was supported by the Defense Acquisition Program Administration and the Agency for Defense Development (UD180018AD).
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2020, International Journal of Production Research