Actual Production System Research Articles

Planning for Attacker Entrapment in Adversarial Settings

In this paper, we propose a planning framework to generate a defense strategy against an attacker who is working in an environment where the defender can operate covertly. Here the objective of the defender is to covertly guide the attacker to a trap state from which the attacker cannot achieve their goal. Further, the defender is constrained to achieve its goal within a K number of steps, where K is calculated as a pessimistic lower bound within which the attacker is likely to not suspect any foul play in the environment. Such a defense strategy is highly useful in real-world systems like honeypots or honeynets where an unsuspecting attacker interacts with a simulated production system while assuming it is the actual production system. Typically, the game between an attacker and a defender is captured using game theoretic frameworks. However, our problem formulation allows us to capture it as a much simpler infinite-horizon discounted MDP where the optimal policy to the MDP gives the defender's strategy against the actions of the attacker. Through empirical evaluation, we show the merits of our problem formulation.

Using Simulation Optimization to Improve the Performance of an Automated Manufacturing Line

As manufacturing capital equipment is expensive, it is necessary that the equipment once in operation is reliable and delivers to the business plan targets. Simulation along with an optimization system is an invaluable tool to confirm that an automated manufacturing line can produce to the required business objectives before and after it goes into operation. Simulation in manufacturing is often applied in situations where conducting experiments on a real system is very difficult often because of cost or the time to carry out the experiment is too long. Optimization is the organized search for such designs and operating modes to find the best available solution from a set of feasible solutions. It determines the set of actions or elements that must be implemented to achieve an optimized manufacturing line. As a result of being able to concurrently simulate and optimize equipment processes, the understanding of how the actual production system will perform under varying conditions is achieved. Implementing the actual changes to equipment to improve reliability can be both time consuming and expensive. Simulation in conjunction with optimization can be used to verify these improvements before the equipment is modified. This study has adopted an open-source simulation tool (JaamSim) to develop a digital model of an automated tray loader manufacturing system in the Johnson & Johnson Vision Care (JJVC) manufacturing facility. This paper demonstrates how this digital model was integrated with SimWrapper optimization and how both tools can be used for the optimization and development of an automated manufacturing line in the medical devices industry.

Simulation and Genetic Algorithms to Improve the Performance of an Automated Manufacturing Line

Simulation in manufacturing is often applied in situations where conducting experiments on a real system is very difficult often because of cost or the time to carry out the experiment is too long. Optimization is the organized search for such designs and operating modes to find the best available solution from a set of feasible solutions. It determines the set of actions or elements that must be implemented to achieve an optimized manufacturing line. As a result of being able to concurrently simulate and optimize equipment processes, the understanding of how the actual production system will perform under varying conditions is achieved. The author has adopted an open-source simulation tool (JaamSim) to develop a digital model of an automated tray loader manufacturing system in the Johnson & Johnson Vision Care (JJVC) manufacturing facility. This paper demonstrates how a digital model developed using JaamSim was integrated with an author developed genetic algorithm optimization system and how both tools can be used for the optimization and development of an automated manufacturing line in the medical devices industry.

A two-stage discrete water wave optimization algorithm for the flowshop lot-streaming scheduling problem with intermingling and variable lot sizes

Considering lot-streaming of different orders in the actual production system, this paper examines the lot-streaming scheduling problem in flowshop production system. Given production sublots of the different jobs allowed to be intermingled in the production process, we take a deeper dive into the flowshop lot-streaming scheduling problem with detached setup and transfer batches for production sublots of jobs. And the mathematical model is presented with the objective of makespan. To tackle the complexity of the problem at hand, a two-stage discrete water wave optimization (TSDWWO) algorithm is proposed to optimize the sublots and sequencing. In the algorithm, a double-wave parallel encoding scheme is designed for two kinds of water waves, which are splitting wave and sequencing wave. Besides, considering the operation effect and time of the algorithm, the corresponding operations during the process of wave propagation are improved for these two kinds of waves respectively. Afterward, the parameters of the proposed TSDWWO are calibrated by the design of experiments approach. To evaluate the performance of the proposed TSDWWO, two different types of test sets are utilized in the experiments, which are the test sets in the literature and test sets randomly generated containing instances of variant scales. Compared with other existing algorithms in the literature, the results show the efficiency of this approach for the flowshop lot-streaming scheduling problem.

UKF-Based State Estimation for Electrolytic Oxygen Generation System of Space Station

Electrolytic oxygen generation system (EOGS) is the only system that can provide oxygen for astronauts in a physicochemical regenerative way in a long-term manned spacecraft. In order to ensure that the astronauts in the cabin can obtain a continuous and enough oxygen supply, it is necessary to carry out real-time condition monitoring and fault diagnosis of the EOGS. This paper deals with condition monitoring and fault diagnosis of the EOGS. Firstly, the dynamic model of the system is established based on the principle electrolysis for actual oxygen production system and the state observer of the system has been designed by using unscented Kalman filter (UKF). The total pressure in the cabin and the partial pressure of oxygen in the electrolytic cell can be observed. Then, considered the actual conditions of the manned space mission with one more astronaut, i.e., 3 astronauts, the simulation experiment is carried out. The simulation results show that the method can effectively estimate the system state, and it is of great significance to ensure the normal operation of the electrolytic EOGS system in the space station.

Development of an architectural-logical model to automate the management of the process of creating complex cyber-physical industrial systems

Modern highly technological production puts forward new requirements and approaches to the implementation of the Industry 4.0 concept. To achieve this, it is necessary to develop a cyber-physical production system that would make it possible to fully take into consideration all the factors of the actual production system. All solutions must pursue the global goal of making the best use of production time and resources, as well as meet the Lean Production concept. Existing ISO-95, 5C, and 8C cyber-physical production systems (CPPS) reference architectures cannot provide clearly expressed systematization and detailing. Such systems are a set of general recommendations that show the interaction processes among the physical and cyber-components of CPPS. This paper reports a new approach to the systemic representation of the processes for managing the development of complex cyber-physical production systems in the face of today's threats. We have suggested a systemic representation of automating the process of managing the development of complex CPPS. Modern threats to the cyber-physical and information and communication systems (ICS) have been considered, which underlie CPPS. An architectural-logical model, as well as methods for automating the CPPS development process management, have been developed. This could help build a logical relationship from the initial target stage to the process of obtaining algorithms at each level and stage of CPPS development as a symbiosis of physical and cyber-components. The devised CPPS development process management model provides an opportunity to propose a group of mathematical models and methods that logically link all development stages into a single rigid hierarchical sequence. This makes it possible to build a single information space with a set of complex CPPS development methodology. The proposed solutions could enable the development of an automated system to manage the process of the development of complex CPPS

A generic hierarchical clustering approach for detecting bottlenecks in manufacturing

The advancements in machine learning (ML) techniques open new opportunities for analysing production system dynamics and augmenting the domain expert's decision-making. A common problem for domain experts on the shop floor is detecting throughput bottlenecks, as they constrain the system throughput. Detecting throughput bottlenecks is necessary to prioritise maintenance and improvement actions and obtain greater system throughput. The existing literature provides many ways to detect bottlenecks from machine data, using statistical-based approaches. These statistical-based approaches can be best applied in environments where the statistical descriptors of machine data (such as distribution of machine data, correlations and stationarity) are known beforehand. Computing statistical descriptors involves statistical assumptions. When the machine data doesn't comply with these assumptions, there is a risk of the results being disconnected from actual production system dynamics. An alternative approach to detecting throughput bottlenecks is to use ML- based techniques. These techniques, particularly unsupervised ML techniques, require no prior statistical information on machine data. This paper proposes a generic, unsupervised ML-based hierarchical clustering approach to detect throughput bottlenecks. The proposed approach is the outcome of systematic and careful selection of ML techniques. It begins by generating a time series of the chosen bottleneck detection metric and then clustering the time series using a dynamic time-wrapping measure and a complete-linkage agglomerative hierarchical clustering technique. The results are clusters of machines with similar production dynamic profiles, revealed from the historical data and enabling the detection of bottlenecks. The proposed approach is demonstrated in two real-world production systems. The approach integrates the concept of humans in-loop by using the domain expert's knowledge.

Determination of Resetting Time to the Process Mean Shift with Failure

All machines deteriorate in performance over time. The phenomenon that causes such performance degradation is called deterioration. Due to the deterioration, the process mean of the machine shifts, process variance increases due to the expansion of separate interval, and the failure rate of the machine increases. The maintenance model is a matter of determining the timing of preventive maintenance that minimizes the total cost per wear between the relation to the increasing production cost and the decreasing maintenance cost. The essential requirement of this model is that the preventive maintenance cost is less than the failure maintenance cost. In the process mean shift model, determining the resetting timing due to increasing production costs is the same as the maintenance model. In determining the timing of machine adjustments, there are two differences between the models. First, the process mean shift model excludes failure from the model. This model is limited to the period during the operation of the machine. Second, in the maintenance model, the production cost is set as a general function of the operating time. But in the process mean shift model, the production cost is set as a probability functions associated with the product. In the production system, the maintenance cost of the equipment and the production cost due to the non-confirming items and the quality loss cost are always occurring simultaneously. So it is reasonable that the failure and process mean shift should be dealt with at the same time in determining the maintenance time. This study proposes a model that integrates both of them. In order to reflect the actual production system more accurately, this integrated model includes the items of process variance function and the loss function according to wear level.

Multi-level approach for important component identification and reliability evaluation for complex system by survival signature

PurposeThe purpose of this paper is to identify the critical components of a complex system by using survival signature. First, a complex system is abstracted with varying scales and generates a multi-levels model. Then reliability evaluations can be conducted by survival signature from rough to fine for tracing and identifying them. Finally, the feasibility of the proposed approach is demonstrated by an actual production system.Design/methodology/approachThe paper mainly applies a multi-level evaluating strategy for the reliability analysis of complex systems with components of multiple types. In addition, a multi-levels model of a complex system is constructed and survival signature also used for evaluation.FindingsThe proposed approach was demonstrated to be the feasibility by an actual production system that is used in the case study.Research limitations/implicationsThe case study was performed on a system with simple network structure, but the proposed approach could be applied to systems with complex ones. However, the approach to generate the digraphs of abstraction levels for complex system has to be developed.Practical implicationsSo far the approach has been used for the reliability analysis of a machining system. The approach that is proposed for the identification of critical components also can be applied to make maintenance decision.Originality/valueThe multi-level evaluating strategy that was proposed for reliability analysis and the identification of critical components of complex systems was a novel method, and it also can be applied as index to make maintenance planning.

Discrete-event simulation of a production process for increasing the efficiency of a newspaper production

One of the characteristics of the newspaper industry is the cycle time of production is limited. The production time cycle is depending on several aspects, namely the quantity of paper produced, as well as the utility of each machine and operator. Because of the cycle time of production is limited, the production process of a newspaper industry is required to have a high level of efficiency so that the level of productivity can be increased. A high level of efficiency can be achieved by optimizing aspects of raw materials, machines, and operators. In this article, the method used for modelling real-time production floor systems is Discrete Event Simulation (DES). DES is done by representing the interaction between all components in the system as an event. Flexsim software used to model the actual production system. Analysis of the results of the simulation conducted to determine the utility level of each machine. In this article, there are three scenarios simulated. Each scenario is replicated ten times. Scenario 1 is the scenario of the current system, then the scenario 2 and 3 are proposed as improvements of composition newspaper production systems. From 2 improvements scenarios, the scenario 3 was chosen to be the best scenario that could improve the efficiency of newspaper production systems.

Assessing the impact of rumen microbial communities on methane emissions and production traits in Holstein cows in a tropical climate

The evaluation of how the gut microbiota affects both methane emissions and animal production is necessary in order to achieve methane mitigation without production losses. Toward this goal, the aim of this study was to correlate the rumen microbial communities (bacteria, archaea, and fungi) of high (HP), medium (MP), and low milk producing (LP), as well as dry (DC), Holstein dairy cows in an actual tropical production system with methane emissions and animal production traits. Overall, DC cows emitted more methane, followed by MP, HP and LP cows, although HP and LP cow emissions were similar. Using next-generation sequencing, it was found that bacteria affiliated with Christensenellaceae, Mogibacteriaceae, S24-7, Butyrivibrio, Schwartzia, and Treponema were negatively correlated with methane emissions and showed positive correlations with digestible dry matter intake (dDMI) and digestible organic matter intake (dOMI). Similar findings were observed for archaea in the genus Methanosphaera. The bacterial groups Coriobacteriaceae, RFP12, and Clostridium were negatively correlated with methane, but did not correlate with dDMI and dOMI. For anaerobic fungal communities, no significant correlations with methane or animal production traits were found. Based on these findings, it is suggested that manipulation of the abundances of these microbial taxa may be useful for modulating methane emissions without negatively affecting animal production.

Improvement of Artistic Cast Production System

AbstractThe paper presents the technology and organization of the artistic cast production. On the basis of the actual cast production system, the manufacturing process was shown, in particular sand–piece moulding, which is a very important process and a time-consuming part of the entire manufacture of the casts. The current state of the production process as well as the organization of the work and production technology were analysed with the use of methods and techniques of production improvement, the Lean Manufacturing concept and computer systems. The results of the analysis and studies were shown with use of schemes and graphs of the layout of the production resources, a flow chart of the production process, value stream mapping, and a costs table for the production and modernization of the moulding stage. The work has shown that there are possibilities to improve the artistic cast production system. This improvement leads to increased productivity, lower production costs of artistic casts and increased competitiveness of the foundry.

Avaliação de Diferentes Taxas de Povoamento sobre o Ganho de Peso de Juvenis de Tambaqui Produzidos em Presidente Médici - Rondônia

In the present study confronted the main stocked densities used actually by the fish farmers for the tambaqui ( Colossoma macropomum ), cultivated at the Presidente Medici municipality (Rondonia, Brazil) in order to verify its influence on the specie growth parameters at the actual production system. Therefore, were evaluated in the period of May to June of 2014, a total of 1,800 juveniles of tambaqui, starting in the end of the advanced juvenile II until the growth phase. During the research period, the fishes were grouped in five repetitions with densities of 60, 80, 100 and 120 individuals, which were subsequent randomly distributed in 20 tanks with 10 m 2 . The fishes feed daily three times with dry fish food with 36% brute protein. Simultaneously, with seven days intervals, the water physicochemical parameters and biometry from the individuals were measured, the last variables were used to calculates the biomass and feed conversion. The limnological variables, when statistically analyzed between the treatments, did not presented significant differences ( p>0.05 ) homogenizing the environmental parameters in the tanks. In the same way, were not significant the differences among the growth variables from the evaluated groups. Thus, was observed that the densities of 12 fishes/m 2 presented bigger biomass (2.35 ± 0.25 kg/m 2 ), suggesting that it is the most recommended density to be used for the regrowth of juveniles’ tambaqui. Keywords : Pisciculture; regrowth; stock densities.

A Co-cooperative Evolutionary Algorithm for Flexible Scheduling Problem under Uncertainty

Abstract Flexible Manufacturing System (FMS) has the characteristics of resources non-uniqueness; the operation can be performed by any available machine in a set of machines. Due to reduce the constraints of the machine, it becomes higher flexible. But it has high complexity existing in the actual production system and making its complexity is higher. We experiment three classical evolution algorithms and two modified evolutionary algorithms with grouping mechanism, and do the experiments under the certain environment on different size of data. We found that as the data growing, the evolutionary algorithms with grouping mechanism can get a better solution with larger probability. In this paper, we propose hybrid evolutionary algorithm based on the particle swarm algorithm combining a set-based grouping and parameter adaptive adjustment mechanism. It is given a set number of available groupings, choose a grouping number and calculate adaptive value, if adaptive value becomes better. Through experiments, we conclude that the proposed hybrid evolutionary algorithm based on co-cooperation gets better solution than evolutionary algorithm and then improve robustness of the proposed algorithm.

Design of reconfigurable automotive framing system

This research introduces new systematic methods dealing with a complete end-to-end design process of the production system. This paper helps product developer and systems engineer to (1) differentiate between product function and added function that are used only for the purpose of manufacturing and assembly process, (2) how these function related to the design parameters in both physical domains for the product design and the production system. Graph network (NW), change propagation index (CPI) and hybrid design structure matrix (HDSM) were introduced to: (1) establish connectivity between sub-systems (modules) before mapping design changes, (2) measure the degree of change to the state of the system due to change propagated through the entire system, (3) estimate how much embedded flexibility is needed for these elements (design variables) to accommodate future changes. A practical example of an actual production system was presented. The hybrid design structure matrix (HDSM) is used to transmit the knowledge gained and detailing the design of the production system.

Calculation of emergy flows within complex chemical production systems

Calculating emergy flows within a typical chemical production system is challenging because it is made up of various interconnected reaction, separation, heating and cooling units with extensive recycle of material and energy. The complexity of the interior structure of a chemical production system, if not carefully considered, could pose problems in emergy calculation. The difficulty is further compounded by the fact that the rules of emergy algebra are somewhat opaque and incomplete. This article shows that complex chemical production systems may be decomposed into four basic structures: series, parallel, bypass and feedback, which can greatly facilitate the process of emergy calculation. Systematic procedures for calculating the emergy flows of the four basic structures without violating the basic rules of emergy algebra are given in detail. Special attention has been paid to the feedback structure, which is analyzed using a novel concept known as virtual emergy flow. An illustrative example based on a hypothetical system made up of the four basic structures and a case study based on an actual polypropylene production system are used to demonstrate the efficacy of the emergy calculation procedures presented in this study.

EXPLORING MORE SUSTAINABLE TECHNOLOGICAL ALTERNATIVES FOR THE GREENHOUSE CUT FLOWERS INDUSTRY IN COLOMBIA

Colombia is the second-largest exporter of flowers in the world. The major production hub is placed around the capital city, Bogota. Approximately 7266 ha are devoted to production of ornamental species under greenhouse conditions, the most important being roses (Rosa spp.) and carnations (Dianthus caryophyllus). Concern about the environmental performance of the industry is growing among the international market. The aim of this work was to explore technological alternatives to reduce the environmental impact exerted by the supply chain (production, marketing and consumption) of cut roses under greenhouse but at the same time looking for a production model that improves actual yields. The Life Cycle Assessment method was used to evaluate the environmental performance of the actual production system as well as a proposed technological alternative. The supply chain was divided into three stages: 1. cropping system including infrastructure, pest management, fertilization, harvest and residues; 2. postharvest including grading, packaging and storage and, 3. transportation to markets in the United States. The number of rose stems produced per square meter of soil was defined as the functional unit. Addition of a heating system to the actual cropping system in order to increase yields and reduce pest incidence was considered. Previous studies have shown that transportation of the flowers by aircraft imposes the major environmental impact by the product. Alternative transportation by ship is discussed in the present study. Results indicated the feasibility of including heating systems actual production schemes due to increase in energy use efficiency. In the overall impact assessment, this alternative will reduce the environmental impact of the actual cropping system. This study demonstrated that technological improvements to the supply chain can result in environmental benefits in order to preserve the competitiveness of the flower industry in Colombia.

Real-Time Data-Based Fault Diagnosis System

Mining from the equipment/technology process historical data can find diagnosis knowledge. Real-time analysis and evaluation on the status of equipment can be realized based on its current state parameters and historical information, which detect the potential fault rapidly and protect equipment to avoid failures further. This paper did an in-depth study in real-time data-based fault diagnosis system, built a real-time data integration platform and accomplished intelligent diagnosis method by ANFIS networks with the mined historical data. The production process was diagnosed and evaluated online with this diagnosis method. Combined with actual production system, its prototype system was developed.

Development of a Web-based Production System for Introductory Cognitive Science Classes

In learning cognitive science, students must learn how to handle an actual production system that runs on a computer. We developed a web-based production system for education that can be used from anywhere such as class rooms, offices, and homes. The system as a web-based application has many advantages as a learning support system. It furnishes students with learning support information for if-clause matching to facilitate learning. We confirmed that our system works sufficiently in a standard computer facility and students learned important features of human cognitive processing by meta-monitoring their own thinking processes.

Simulation modeling and analysis for production scheduling using real-time dispatching rules: A case study in canned fruit industry

This paper considers a production scheduling problem frequently found in many industries whose raw materials are agricultural products. The study focuses on a production system in processed canned fruit industry as a case study. Common characteristics of the system include: (1) high uncertainties of agricultural raw materials (fresh fruits), both in terms of quality and quantity, which significantly affect the production schedule that is usually planned in advance, (2) multiple types of finished products (can sizes and fruit types), sharing the same resources, thus makes their scheduling interdependent, and (3) the shared resources (retorts) are non-identical which exist to provide services to the bottleneck operation (sterilization) in parallel. The paper has two interrelated objectives: to propose the use of real-time scheduling methods based on dispatching rules for such systems, and to demonstrate the use of computer simulation modeling to imitate the actual production system and how to conduct computational experiment on the simulation model to determine a set of appropriate dispatching rules for the case study industry. Nine real-time, setup dependent, dispatching rules are compared using two types of performance measures: flow time and tardiness. The results show the effectiveness of this approach to supporting the decision-making process in production scheduling of canned fruit products.