Low carbon manufacturing: Characterization, theoretical models and implementation

Today, the rising of carbon dioxide (CO2) emissions is becoming the crucial factor for global warming especially in industrial sectors. Therefore, the research to reduce carbon intensity and enhance resources utilization in manufacturing industry is starting to be a timely topic. Low carbon manufacturing (LCM) can be referred to the manufacturing process that produces low carbon emissions intensity and uses energy and resources efficiently and effectively during the process as well. In this paper, the concepts of LCM are discussed and the LCM associated theoretical models, characterization and implementation perspective explored. The paper is structured in four parts. Firstly, the conception of low carbon manufacturing is critically reviewed then the characterization of low carbon manufacturing is discussed and formulated. Third part, the theoretical models are developed with initial models by using the theory from supply chain modeling and linear programming solutions (LP). The models show the relationship of resource utilizations and related variables for LCM in two levels: shop-floor and extended supply chain. Finally, the pilot implementations of LCM are discussed with two approaches: desktop or micro machines and devolved manufacturing. The paper is concluded with further discussions on the potential and application of LCM for manufacturing industry

Mixed-load machine utilization improvement and transfer batch size optimization using hybrid simulation approach

Current technological development has increased the competitiveness in the manufacturing system, especially for the electronic industry. This research is based on case company in the automatic testing and label printing processes of a multinational hard disk drive (HDD) manufacturing system with the objective of improving the tester utilization while achieving the production target. The problem is complex as the testers are employed to simultaneously load multiple product families. Each product family has several models with different testing durations. In addition, apart from the high product mixes for each product family undergoes different process flow making the problem more complicated. The company has difficulty to achieve the targeted tester utilization of 96%, as the current utilization is 71.14%. As the problem is too complicated to be solved by an analytical method, a hybrid simulation approach was employed to solve the operation machine allocation and the transfer batch size problem. Firstly, the problem of mixed-load tester was formulated through a mathematical model. Then, a simulation model was designed and developed to evaluate the scenarios of the mixed-load tester configurations. After that, the multi criteria decision making techniques were employed to determine the best scenario. Finally, the transfer batch size was optimized to improve system WIP. The final proposed configuration successfully increased the tester utilization by 24.89% and reduced the number of testers by 37.77% for Tester A and by 27.27% for Tester B while improving the throughput by 6.88% compared to the current system. In addition, the transfer batch size was reduced from 120 units to 86 units and system WIP was successfully reduced by 6.43%

Analog to Digital Workflow Improvement: A Quantitative Study

This study tracked a radiology department’s conversion from utilization of a Kodak Amber analog system to a Kodak DirectView DR 5100 digital system. Through the use of ProModel(®) Optimization Suite, a workflow simulation software package, significant quantitative information was derived from workflow process data measured before and after the change to a digital system. Once the digital room was fully operational and the radiology staff comfortable with the new system, average patient examination time was reduced from 9.24 to 5.28 min, indicating that a higher patient throughput could be achieved. Compared to the analog system, chest examination time for modality specific activities was reduced by 43%. The percentage of repeat examinations experienced with the digital system also decreased to 8% vs. the level of 9.5% experienced with the analog system. The study indicated that it is possible to quantitatively study clinical workflow and productivity by using commercially available software

Simulation of mixed-load testing process in an electronic manufacturing company

The automatic testing machine, called by mixed-load tester, has ability to load and test multiple product families in different testing durations simultaneously. However, the high product mixes for each product family undergoes a different process flow. In addition, the capability of the robot inside tester used for loading and unloading a product to each slot makes the capacity planning problem more complicated. It effects low tester utilization. This paper developed simulation models of capacity planning scenarios under demand and testing time uncertainty. These scenarios are built by robust optimization to handle worst case condition. The result shows the proposed solutions gives better tester utilization and improves the decision making process by providing more detailed and precise information about capacity planning under uncertainties that was not available in company`s current method. To the best of our knowledge, this developed model is the first one considering the mixed–load tester under uncertainties

Simulasi Optimasi Antrian Truk Pada Proses Loading Sembako Gudang PT.XYZ

Gudang memiliki peranan penting bagi perusahaan, tak terkecuali PT. XYZ yang berlokasi di Jakarta Utara. Salah satu kegiatan operasional yang dilakukan di gudang PT. XYZ adalah proses loading sembako ke truk angkut. Namun, waktu yang dibutuhkan oleh setiap truk angkut untuk melakukan proses loading sembako dapat mempengaruhi jumlah truk angkut yang menunggu untuk dilayani. Penelitian ini bertujuan untuk meminimasi waktu truk angkut pada proses loading sembako di gudang PT. XYZ menggunakan metode simulasi optimasi. Hasil penelitian mengindikasikan bahwa jumlah truk angkut yang dapat dilayani dapat ditingkatkan dengan menambah jumlah dock door. Berdasarkan percobaan simulasi optimasi, penelitian ini mengusulkan 32 dock door untuk melayani kegiatan loading sembako di gudang PT. XYZ yang dapat mengurangi waktu rata-rata pelayanan truk Fuso dan truk CDD masing-masing sebesar 76.3 menit dan 73.45 menit. Selain itu, utilitas di parking line 1 dapat berkurang hingga 9.2 % dan 48.39 % di parking line 2

An Intelligent Simulation Environment for Manufacturing Systems

The manufacturing field is an area where the application of simulation is an essential tool for validating methods and architectures before applying them on the factory floor. Despite the fact that there are a great number of simulation tools, most of them do not take into account the specific requirements of the new manufacturing era such as distributed organization, interoperability, cooperation, scalability, fault tolerance and agility. On the other hand, Multiagent System technology has demonstrated its utility in manufacturing system modeling and implementation. Agenthood features such as proactivity, reactiv- ity, and sociability may also be useful for associating them with the specific simulation needs of the new changing requirements for manufacturing systems. In this paper, an Agent-supported Simulation Envi- ronment for intelligent manufacturing systems is presented. The different roles that are played by the agents of the simulation environment are defined taking into account the specific dynamic features in manufacturing simulation and the requirements of the new manufacturing era. Moreover, the interaction and cooperation scenarios among these agents are specified to facilitate manufacturing simulation in an appropriate and flexible way. A detailed evaluation study, with regards to the new manufacturing era requirements, demonstrates the advantages of the proposed approach over current state-of-the-art proposals.Ruíz Vega, N.; Giret Boggino, AS.; Botti Navarro, VJ.; Feria, V. (2014). An Intelligent Simulation Environment for Manufacturing Systems. Computers and Industrial Engineering. 76:148-168. doi:10.1016/j.cie.2014.06.013S1481687

Stochastic Models For Enhancing Agility of Supply Chains

This paper deals with the application of stochastic inventory model to the three-tier supply chain and verifying the values obtained by mathematical model with discrete event simulation. We investigate three-stage serial supply chain with stochastic demand and fixed replenishment lead-time. Inventory holding costs are charged at each stage, and each stage may incur a consumer backorder penalty cost charged by primary supplier to secondary supplier. The customer-demand follows Poisson distribution. We implement Base Stock model for inventory control at both suppliers. Computer simulation is then designed in such a way that it satisfied all the assumptions for mathematical model. Simulation is run to validate the results obtained from the mathematical model

Production line: effect of different inspection station allocation under accepts reject inspection policy

Manufacturing system is one of the most important parts in any organization as it produces the output of the company which will generate the profit. It consists partly of the production line which plays the role as the centre of production to create the end product which could be half finished or the full product. It is a big problem for the company to determine which is the better arrangement and combination of the tools or machines available in this area of the organization as different combination will greatly impact the productivity of the production line together with the profit of the company. This research intend to analyze a new production line in a metal stamping company based on the complain from the company and try to explore the better layout or arrangement in the production line in reflect to the complained problem and constrain of the provided of accept the defect and repair inspection policy. The production line is first being analyzed in response to complain through computer simulation. After the problem had been identified, the researcher tried different alternatives in the attempt to seek for the better layout or arrangement in the production line. The effect of different inspection station allocation layout is then being evaluated in term of the production time. The research has resulted in the finding of the cause for the long production time in the factory which is the long inspection steps which consumed much of the production time. After a few alternatives have been explored in allocating the inspection station, it is obvious that the current approach of the production line is the better one. Even by reducing the number of inspection station, interesting enough, the production time does not seem to decrease but yet increased. This finding contradicts the normal thought of fewer stations means shorter time. This finding could be the founding basic in the future research regarding the allocation of the inspection station following certain provided policy. This is also very helpful in real life practice in company as to help them improve their production time. As for the time being, there is yet a research addressing this issue pertaining the given inspection policy

Definition, Analysis, And An Approach For Discrete-Event Simulation Model Interoperability

Even though simulation technology provides great benefits to industry, it is largely underutilized. One of the biggest barriers to utilizing simulation is the lack of interoperability between simulation models. This is especially true when simulation models that need to interact with each other span an enterprise or supply chain. These models are likely to be distributed and developed in disparate simulation application software. In order to analyze the dynamic behavior of the systems they represent, the models must interoperate. However, currently this interoperability is nearly impossible. The interaction of models also refers to the understanding of them among stakeholders in the different stages of models¡Š lifecycles. The lack of interoperability also makes it difficult to share the knowledge within disparate models. This research first investigates this problem by identifying, defining, and analyzing the types of simulation model interactions. It then identifies and defines possible approaches to allow models to interact. Finally, a framework that adopts the strength of Structured Modeling (SM) and the Object-Oriented (OO) concept is proposed for representing discrete event simulation models. The framework captures the most common simulation elements and will serve as an intermediate language between disparate simulation models. Because of the structured nature of the framework, the resulting model representation is concise and easily understandable. Tools are developed to implement the framework. A Common User Interface (CUI) with software specified controllers is developed for using the proposed framework with various commercial simulation software packages. The CUI is also used to edit simulation models in a neutral environment. A graphical modeling tool is also developed to facilitate conceptual modeling. The resulting graphic can be translated into the common model representation automatically. This not only increases the understanding of models for all stakeholders, but also shifts model interactions to the ¡§formulating¡š stage, which can prevent problems later in the model¡Šs lifecycle. Illustration of the proposed framework and the tools will be given, as well as future work needs