Existing Production Systems Research Articles

АНАЛИЗ ПРОБЛЕМ И ОПРЕДЕЛЕНИЕ ПУТЕЙ РАЗВИТИЯ ПРОИЗВОДСТВЕННЫХ СИСТЕМ АВТОМОБИЛЬНОГО ПРОИЗВОДСТВА

The article presents the results of the analysis of the current problems of the existing production systems of automobile production of domestic automakers. A comprehensive approach is proposed to overcome the identified problems, taking into account the best practices of world leaders in the industry.

Extraction of Keywords for Retrieval from Paper Documents and Drawings based on the Method of Determining the Importance of Knowledge by the Analytic Hierarchy Process: AHP

Extraction method of keywords for retrieval from paper documents and drawings based on the method of determining the importance of knowledge by the Analytic Hierarchy Process: AHP method is proposed. The method allows distinguish the documents into three categories, letter, form and drawing types of documents, then the most appropriate knowledge about keyword for retrievals, font size, location, frequency of the words etc. are selected for each document type. Production rules are created with more than five of the knowledge on keywords for retrievals. Traditional production system employs isolated knowledge so that it is not easy to take overall suitability of the knowledge. In order to overcome this situation, AHP is employed in the proposed system. Through experiments with 100 documents and diagrams, 98% success rate is achieved, and it is found that appropriate candidates for keywords with likelihood or certainty factor can be extracted with the proposed system. The proposed production system shows 50% of improvement on success rate of the keywords extraction from documents and diagrams compared to the existing production system without AHP.

Line Balancing and Sequencing for Peak Power Minimization

In the past years, environmental awareness started to bring new production paradigms based on energy efficiency. If it is possible to improve energy efficiency of existing production systems, it should be even more profitable to consider this objective at the design stage. In the context of Paced Production Lines, and given power requirements for operations, it becomes possible to assign more efficiently these operations to stations while respecting other constraints such as maximum takt time and number of workstations. The repetitive nature of paced lines implies that misconceptions implying a high peak power consumption will see this peak power repeated over and over without having large possibilities to correct it. In order to tackle peak power minimization objectives, this implies to consider sequencing of operations in addition to their assignment to workstation which is not classical in line balancing. In this paper, the problem under study is presented with a new specific feature that allows to consider semi-active sequence of operations at each station. In order to address large scale instances, a first metaheuristic approach is implemented and evaluated on an extended dataset from the literature. Results show that it is possible to improve energy efficiency at the design stage of production systems.

Evaluation and Improvement of Manufacturing System Using Computer Software Arena

The main purpose of the paper is to identify the controllability of an existing production system; yogurt production line in Abu Ghraib Dairy Factory which has several machines of food processing and packing that has been studied. Through the starting of analysis, instability in production has been found in the factory. The analysis is built depending on experimental observation and data collection for different processing time of the machines, and statistical analysis has been conducted to model the production system. Arena Software is applied for simulating and analyzing the current state of the production system, and results are expanded to improve the system production and efficiency. Research method is applied to contribute in knowing and expecting the future running of the system to enhance the controllability of the system production and improve the production system and machine efficiency. Moreover, built an experiment-real model in Arena in order to control the system in term of production and process. First step is to collect the statistical data required for analysis in terms of input and output data for analysis. Second, is to track the production problem in term of process bottleneck in order to improve the utilization of the system. Third is to validate the model in order to overcome the product demand of the system uncontrollability. Through the result analysis of waiting time and production rate, it is clearly shown that system is stable with a need to resetting the capacity as a chance for the improvement, regarding to resources utilization. Re-planning resources capacity positively enhances the production and profitability of the system.

Determinants of market outlet choices by smallholder teff farmers in Dera district, South Gondar Zone, Amhara National Regional State, Ethiopia: a multivariate probit approach

In Ethiopia, teff is an important cereal crop, particularly in Dera district. It is a source of food and provides cash income for majority of smallholder farmers. To commercialize teff producers, selecting an appropriate market channel is mandatory. However, selecting an appropriate market channel is not an easy task because there are different factors that influence market outlet choices. Therefore, this study aimed to identify factors that influence teff market outlet choices. A two-stage random sampling procedure was used and a total of 154 smallholder farmers were randomly and proportionally selected to collect primary data. Multivariate probit model was employed to identify factors affecting teff market outlet choices. The result of the study shows that the probability of teff producers to choose wholesaler, retailer, consumer and cooperative market outlets was 31.82%, 35.71%, 37.01% and 16.88%, respectively. This shows that consumer was the most likely chosen market outlet while cooperative was the less likely chosen market outlet. The joint probability of farmers to choose the four market outlets is (0.1%) lower than the likely of no choosing four market outlets (19.5%). The result of multivariate probit model revealed that age of household head, land size, quantity of teff produced, lagged price of teff, family size (AE), membership of cooperatives and distance to the nearest market were found to be statistically and significantly affecting the market outlet choice behavior of teff producers. This implies that improving the production capacity of farmers and invests on rural cooperatives would help smallholder farmers to choose the rewarding market outlet. Therefore, the study suggested that improving the existing production system, farmers relying on intensive cultivation; giving better price for farmers and being membership of cooperative are important strategies to select the appropriate market channel.

Life cycle assessment of 3D printing geo‐polymer concrete: An ex‐ante study

AbstractThree‐dimensional (3D) printing and geo‐polymers are two environmentally oriented innovations in concrete manufacturing. The 3D printing of concrete components aims to reduce raw material consumption and waste generation. Geo‐polymer is being developed to replace ordinary Portland cement and reduce the carbon footprint of the binder in the concrete. The environmental performance of the combined use of the two innovations is evaluated through an ex‐ante life cycle assessment (LCA). First, an attributional LCA was implemented, using data collected from the manufacturer to identify the hotspots for environmental improvements. Then, scaled‐up scenarios were built in collaboration with the company stakeholder. These scenarios were compared with the existing production system to understand the potential advantages/disadvantages of the innovative system and to identify the potential directions for improvement.The results indicate that 3D printing can potentially lead to waste reduction. However, depending on its recipe, geo‐polymer likely has higher environmental impacts than ordinary concrete. The ex‐ante LCA suggests that after step‐by‐step improvements in the production and transportation of raw materials, 3D printing geo‐polymer concrete is able to reduce the carbon footprint of concrete components, while it does still perform worse on impact categories, such as depletion of abiotic resources and stratospheric ozone depletion. We found that the most effective way to lower the environmental impacts of 3D concrete is to reduce silicate in the recipe of the geo‐polymer. This approach is, however, challenging to realize by the company due to the locked‐in effect of the previous innovation investment. The case study shows that to support technological innovation ex‐ante LCA has to be implemented as early as possible in innovation to allow for maintaining technical flexibility and improving on the identified hotspots.

Smart Factory Reference Model for Training on Industry 4.0

Technological disruption and rising labour costs are impacting the future of manufacturing in Malaysia and its competitive position. Nevertheless, the understanding on smart manufacturing in the context of Industry 4.0 is still lacking in the academia and industry. Thus, this work describes the development of a smart factory reference model as a guide to upgrading an existing production system towards the vision of Industry 4.0 using readily available components. The reference model consists of (i) a principle solution describing the concept of a smart factory and (ii) a working prototype demonstrating the functionality of a smart factory. The smart factory prototype is a modular production system connected to a server accessible locally or through the internet and able to produce up to eight variants of a product. The SCADA software was used to interface various systems together and create the user interface. The prototype was evaluated using VDMA Industry 4.0 Toolbox. This work provides a way to integrate theory and practical Industry 4.0 applications into tertiary education curricula. It showcases the potential applications, benefits and proof of concept of new technologies for industry adoption.

Recycling Agricultural Wastes and By-products in Organic Farming: Biofertilizer Production, Yield Performance and Carbon Footprint Analysis

The Circular Economy concept implies the re-design of existing production systems in agriculture, by promoting agricultural waste recycling. In an organic zucchini—lettuce rotation, two different agroecological tools were considered: biofertilizer and presence or absence of green manure (GM+ and GM−). In particular, we compared: (i) anaerobic digestate from cattle manure, co-composted with vegetable wastes, with the presence of GM (AD GM+); (ii) olive pomace compost, re-composted, with the presence of GM (OWC GM+); (iii) municipal waste compost with GM (MWC GM+); (iv) municipal waste compost without GM (MWC GM−). These materials were tested with a commercial organic fertilizer without GM (COF GM−) as a positive control. The objectives were: (i) assessing the environmental sustainability of biofertilizers through carbon footprint analysis by greenhouse gas—GHG—emissions; (ii) evaluating the agronomic performance on the vegetable rotation, by energy output assessment. The total carbon emissions of biofertilizers production was 63.9 and 67.0 kg of CO2 eq Mg−1 for AD and OWC, respectively. The co-composting and re-composting processes emitted 31.4 and 8.4 kg CO2 per Mg of compost, respectively. In AD the ventilation phase of composting accounted for 37.2% of total emissions. The total CO2 emission values for the two-crop cycles were the highest in COF GM− and the lowest in OWC GM+, due to different fertilizer sources. On the average of the treatments, the input that induced the highest CO2 emission was irrigation (37.9%). The energy output assessment for zucchini and lettuce highlighted similar performance for all the treatments. Our findings demonstrated the validity of the tested processes to recycle agro-industrial wastes, and the potential of agroecological practices (GM) to mitigate GHG emissions.

Method for digital evaluation of existing production systems adequacy to changes in product engineering in the context of the automotive industry

Current industry practices during the Product Development Process (PDP) still points to the isolation of knowledge domains even with the increase of digitalization. Considering manufacturing process constrains from the beginning of the PDP avoids problems in later stages during the whole product life cycle. Through the application of concepts of the Digital Thread approach, the opportunity to intelligently integrate knowledge into product development is presented, creating a “digital fabric” capable of directing and supporting all stages of the product life cycle. Through these concepts, this research proposes the elaboration of an ontological model and application method capable of evaluating, in real time, the adequacy of the existing production systems, integrating the project and process information. The methodological framework used for the development of this method was Design Science Research. In this way, six steps were performed: (i) problem identification and motivation; (ii) definition of the objectives of the solution; (iii) artifact design and development; (iv) demonstration; (v) evaluation; and, (vi) results report. Through the description of manufacturing systems, the solution contributes to the digital evaluation and facilitates the decision making regarding productive systems, as well as data recovery, reutilization and management. In order to do an initial framework validation, it was performed the application of adequacy principles of a specific production line in automotive sector. However, this choice of a complex industry sector translates a clear possibility of framework adaptation to another industrial segment.

Caliper

We introduce Caliper , a technique for accurately estimating performance interference occurring in shared servers. Caliper overcomes the limitations of prior approaches by leveraging a micro-experiment-based technique. In contrast to state-of-the-art approaches that focus on periodically pausing co-running applications to estimate slowdown, Caliper utilizes a strategic phase-triggered technique to capture interference due to co-location. This enables Caliper to orchestrate an accurate and low-overhead interference estimation technique that can be readily deployed in existing production systems. We evaluate Caliper for a broad spectrum of workload scenarios, demonstrating its ability to seamlessly support up to 16 applications running simultaneously and outperform the state-of-the-art approaches.

Ina

This study is conducted to better understand the potential of purun weaving as a suitable business approach that could support peatland restoration in South Sumatra. It aims to analyze the obstacles of purun weaving and its market potential as green products. This study applies qualitative and quantitative methods, including in-depth interviews and surveys. The in-depth interviews invove local business actors in Pedamaran Sub-district, Ogan Komering Ilir Regency (i.e. harvesters, weavers, and traders) and the policy-makers. Online and intercept surveys are conducted to analyze current condition and market potential of purun handicrafts, especially as the example of green products. Identified challenges include lack of market knowledge and connections, unstable supply of raw materials, lack of financial capitalization, and low product quality. The market potential for green products, however, is highly promising, as more than 80% of respondents are willing to pay a higher price for these products. Gaps between existing production system and market potential could be narrowed down by adjusting policies for existing peat swamp areas, improving access to microfinance, and implementing specific capacity building for the weavers. Moreover, suitable marketing strategies are required to support the business sustainability of purun weaving.

A digital twin for production planning based on cyber-physical systems: A Case Study for a Cyber-Physical System-Based Creation of a Digital Twin

The increasing change of production leads to differences between the current shop floor and the state of planning. This difference causes significant challenges for production planners while integrating new products into existing production systems. To tackle this issue, this paper presents a concept for the automated creation of a digital twin of a body-in-white production system based on current resources, products as well as process information from the cyber-physical system. The paper focuses on the different data sources and information in cyber-physical systems necessary for integration planning. Furthermore, major parts of the concept are evaluated in a real body-in-white production system. The resulting digital twin enables faster product integration and Industry 4.0 concepts.

Feasibility of Using Simulation Technique for Line Balancing In Apparel Industry

Abstract Line balancing is a crucial task for manufacturing companies in order to improve productivity and minimize production costs. Different analytical and heuristic/metaheuristic methods have been used for solving Assembly Line Balancing Problems (ALBP) for many years in manufacturing industries. Computer simulation is a new technique which has got interest by some researchers, since last few decades. Unlike the other techniques, computer simulation enables one to manage the stochastic nature of system variables. However, literature reviews revealed that only few system variables have been taken into consideration in research works that have been conducted so far. This paper aims at extending the studies on application of computer simulation technique for line balancing in apparel industries. A garment style (ladies’ tunic) which has 54 operations was observed for experimentation. Sixty two operators are involved in existing production system. ARENA® simulation software was used for system modelling and simulation purpose. Model validation is accomplished through hypothesis test including about eight different system variables. After model validation five different ‘what-if’ scenarios are evaluated for reconfiguration of the assembly line.

Review Article on Mushroom Cultivation

Edible mushrooms are collected from the wild. They are currently threatened by deforestation. A survey was carried out and to gather information on their household consumption, income generation and to determine how their cultivation could improve rural livelihood. Mushrooms are sources of food, income and of medicinal value. The market for mushrooms continues to grow due to interest in their culinary, nutritional, and health benefits. They also show potential for use in waste management. However, as fungi, mushrooms have life cycles very different from those of green plants. The choice of species to raise depends both on the growth media available and on market considerations. Oyster mushrooms, which grow on many substrates, are easiest for a beginner. Shiitake mushrooms already have earned considerable consumer demand. Only two mycorrhizal mushrooms, morels and truffles, have been commercially cultivated. Mushroom cultivation offers benefits to market gardens when it is integrated into the existing production system. A careful analysis of potential markets must be the first step in deciding whether to raise mushrooms to sell. Mushrooms are cultivated only on small scale but efforts are underway to extend improved methods of its cultivation to the rural communities, thereby providing them with alternative livelihood and thus ease the pressure on the forests.

Which Channel to Ask My Question?: Personalized Customer Service Request Stream Routing Using Deep Reinforcement Learning

Customer services are critical to all companies, as they may directly connect to the brand reputation. Due to a great number of customers, e-commerce companies often employ multiple communication channels to answer customers' questions, for example, chatbot and hotline. On one hand, each channel has limited capacity to respond to customers' requests, on the other hand, customers have different preferences over these channels. The current production systems are mainly built based on business rules, which merely considers tradeoffs between resources and customers' satisfaction. To achieve the optimal tradeoff between resources and customers' satisfaction, we propose a new framework based on deep reinforcement learning, which directly takes both resources and user model into account. In addition to the framework, we also propose a new deep-reinforcement-learning based routing method-double dueling deep Q-learning with prioritized experience replay (PER-DoDDQN). We evaluate our proposed framework and method using both synthetic and a real customer service log data from a large financial technology company. We show that our proposed deep-reinforcement-learning based framework is superior to the existing production system. Moreover, we also show our proposed PER-DoDDQN is better than all other deep Q-learning variants in practice, which provides a more optimal routing plan. These observations suggest that our proposed method can seek the trade-off where both channel resources and customers' satisfaction are optimal.

Methodical approach for the development of a platform for the configuration and operation of turnkey production systems

Shorter product lifecycles lead not only to faster time-to-market for products but also to the need for just as fast available associated production systems. These shorter product lifecycles, as well as the increasing individualization of products, also result in further decreasing production lot sizes. Young companies in China in particular are characterized by a very high speed of innovation but may not have the necessary manufacturing knowledge or capacities to bring their developed products to the market with a scalable production. For this reason, there is a great need to quickly set up and commission turnkey production systems or to reconfigure existing production systems for new production tasks in the shortest possible time. This paper describes the design and architecture of a cloud platform with the aim to support a manufacturer independent design process for turnkey production systems. This process ranges from the product to be manufactured to the operation of the production system. Firstly, the structure and methodology used to link the various objectives are discussed. The system for recording and structuring product and production system data to create reusable modules from components and machines is described. Subsequently, the use of standardized modules is developed to support reconfiguration of the production system during operation. In addition, the digital business models tailored to the production system are proposed to the platform user for commissioning and operation of the plant. A case study is conducted to validate the proposed methodology.

Data map – method for the specification of data flows within production

Digitization of production offers potentials e.g. in reducing throughput-times and increasing productivity. MES and ERP systems can be the central hub for organizing, analyzing and processing enterprise and manufacturing data. Introducing these systems requires clear requirement-definition, since 60% of errors occur here. Even for existing production systems, the successful leverage of data potentials requires a systematic overview of data sources, processing units and sinks.We propose a Data Map to address these problems. It visualizes data flow between data sources and software systems, considering their properties and process context. We demonstrate the application in a project to identify requirements for selecting an ERP System.

Indigenous Smallholder Farming Strategies in South-Western Burkina Faso in Climate Variability Context

Existing production systems in West Africa are unable to maintaining a good enough nutrient cycling at farm level. Climate change is expected to increase food production issues in agro ecosystems. Adaptation of smallholders to climate change requires rethinking and adjusting their existing production systems in order to improve their nutrient balance and to ensure an efficient provision of food demand. To that end, better understanding indigenous strategies is still needed. The present study was conducted in South-western Burkina Faso. Three communities of the province were chosen through a cluster analysis using NDVI index, land use map, soil degradation information, and population density. Using soil map, six villages were randomly selected and 360 farms were surveyed. The findings show that farmers overwhelmingly (99%) perceive rainfall variability in the studied zone. Farmers used in average 22.69 ± 3.11 kg ha -1 of mineral fertilizer. A total of 28.06 % and 23.6% of interviewed farmers were using farm yard manure and compost from crop residues, respectively. Stone bunds were implemented by around 35% of farmers. The study also showed that most farmers rely on non-scientific methods for determining sowing period. The study demonstrates the need for rethinking the policy intervention strategies to ensure a better uptake of proven practices in sustainable nutrient management, and to build capacities of smallholder farmers in agro-meteorology to guide the decision making.

Cold standby renewal process integrated with environmental factor effects for reliability evaluation of multiple autonomous robot system

PurposeThe purpose of this paper is to estimate the required number of robots consisting of some non-repairable components, by employing a renewal model. Considering the importance of the availability of standby autonomous robots for reducing and preventing down-times of advanced production systems, which imposes a considerable loss, the present research tries to introduce a practical model for the determination of the required number of autonomous robots.Design/methodology/approachMost of the available research on the estimation of the required standby components based on the reliability characteristics of components has not considered the environmental factors influencing the reliability characteristics. Therefore, such estimations are not accurate enough. In contrast, this paper focuses on the influence of the environmental and human factors (e.g. the operators’ skill) on the robot reliability characteristics.FindingsA model based on the Weibull renewal process combined with the cold standby strategy is developed for reliability evaluation of the system. The effectiveness of the proposed integrated reliability evaluation model is worked out in some cases.Originality/valueDetermining a required number of robots is an important issue in availability and utilization of a complex robotic production system. In an advanced production system, while the estimation process of a required number of robots can be performed through different approaches, one of the realistic estimation methods is based on the system’s reliability that takes into consideration the system operating environment. To forecast the required number of robots for an existing production system, in some cases, the assumption of a constant failure rate does not differ much from the assumption of a non-constant failure rate and can be made with an acceptable error.

Physical Attributes of the Soil and Maize Productivity Under an Intercrop System

The intensive use of agricultural areas for farming, together with inadequate management, can cause soil degradation and promote a low-quality environment for crops; An intercrop system of maize and forage can therefore be an alternative to existing production systems. The aim of this study was to identify the effect of intercropping maize with forage on the physical attributes of the soil and on productivity in maize, as a function of the sowing season and different forages, in the northeastern region of Brazil. A trial intercrop of maize with three forages (Brachiaria brizantha, Panicum maximum ‘Mombasa’, and Crotalaria spectabilis a.) was planted at two different times: phase 1-forage sown between the rows of maize, mixed with the basal dressing; and phase 2-forage sown between the rows, at the V4 stage in maize; in addition to maize with no intercrop (control). The trial was carried out in a randomised block design, with four replications. Forage Mombasa inserted in phase 1 (1) and phase (2) of sowing favored higher values of macroporosity in the layers 0.0-0.10 m and 0.10-0.20 m respectively. For the mass of 1000 grains and grain yield, there were no significant differences between the treatments when compared to the exclusive corn. It was concluded that the maize-forage intercrop promotes changes in the physical attributes of the soil (macroporosity, total porosity and density), and that maize productivity is not affected by the intercrop system.