Production Planning Activities Research Articles

Integration of coupled sectors decarbonization pathways across the value chain into corporate carbon management processes

To contribute to the mitigation of climate change, a significant number of businesses from a wide range of sectors increasingly commit to science-based carbon reduction targets. However, to integrate their ambition into strategic and operational business processes, companies often merely rely on historically determined emission data. These data provide limited support in forecasting the company's future product emissions within the framework of corporate carbon controlling. This implies for example that windfall gains from regulatory and individual decarbonization efforts in coupled sectors can only be forecasted to a limited extent. Yet, for a more reliable basis for decision making, not only proactive product planning but also scenario pathways on how coupled business sectors will progress must be incorporated. Especially for companies with complex, globalized supply chains highly dependent on raw materials, this leads to a more dependable analysis of the carbon hot-spots to be tackled. Therefore, based on an analysis of current corporate carbon management practices, a framework is elaborated to expand corporate carbon controlling to coupled sectors and their decarbonization pathways. This includes a method to integrate decarbonization forecasts of coupled sectors within a company's product planning activities. This method is illustrated with an exemplary case study, in which the product related emissions of a fictive automotive manufacturer are forecasted between 2020 and 2050 using product portfolio projections and coupled sector decarbonization. The latter leads to an overall company's carbon emissions reduction in 2050 by about 77% in comparison to the prediction neglecting external sustainability aspirations and thus emphasizes the importance of capturing these effects.

The effect of demand forecasting choices on the circularity of production systems: a framework and case study

Designing Circular Economy systems needs previous decisions that depend on Planning and Operation decisions. One of these decisions relates to the forecasting demand method, because it scales the needs of the production flow and the necessary resources. This study investigates how the selection of forecasting methods affects the circularity of production systems and shows a case study of particleboard manufacturers. Scenarios with different parameters were tested. Results showed an increase in the Material Flow Analysis (MFA) indicators between the methods Linear Regression initiation (HW-LR) vs. Extended Additive Holt-Winters (EAWH) and variations in the MCI when restrictions on supply capacity are added in terms of recycled raw material use. Also, a positive correlation was found between the error rate in demand forecasting and MCI. These results highlight the relevance of choosing the forecast method due to its impact on production planning activities and environmental performance toward a more circular production system.

One-of-a-kind production (OKP) planning and control: a comprehensive review and future research directions

PurposeThe aim of this paper is to identify some specificities of production planning and control (PPC) activities in the one-of-a-kind-production (OKP) process through an extensive literature review. Relevant aspects related to systems and PPC activities in the context of OKP environment are discussed, and six opportunities for future research are highlighted.Design/methodology/approachThe following research is based on a review of 53 articles published in peer-reviewed journals over the past three decades. After an initial descriptive analysis based on bibliometric indicators, a cluster analysis of 15 most cited articles was carried out using multivariate data analysis techniques and in-depth analysis.FindingsThe results reveal some specificities inherent to the clusters featured in the research, including aspects of planning, control and systems for OKP process. This cluster addresses information regarding next-generation manufacturing systems, scheduling and design science, computer simulation and project approach. On the other hand, the authors point out six topics for future research regarding contemporary issues associated with PPC in the context of OKP.Originality/valueThis paper fills an important gap regarding OKP production planning and control practices. The results provide a theoretical overview of different PPC practices suitable for the OKP environment. Furthermore, it can provide insights for scientific developments in order to manage the complexity inherent in the OKP process.

An Integrated Production and Distribution Planning Model in Shrimp Agroindustry Supply Chain

This study discusses the integration model of production and distribution planning in the shrimp agroindustry supply chain, consisting of four echelons: shrimp suppliers, shrimp agroindustry, logistics provider companies, and buyers. The shrimp agroindustry supply chain is an essential part of the supply chain of processed product food, which transforms raw shrimp into various processed shrimp frozen products. One form of collaboration between supply chain actors is the integration of production and distribution planning activities. A model is developed to determine the flow of goods from each echelon, the number of processed shrimp products in the agroindustry, and the supplies of processed shrimp products. The bi-objective mixed-integer linear programming is proposed to describe the characteristics of the problem to minimize the total supply chain costs and maximize service level. Non-dominated sorting genetic algorithm II (NSGA-II) is designed to solve the shrimp agroindustry supply chain problem. The sample problem from the shrimp agroindustry in East Java, Indonesia, is applied to exhibit an algorithm’s efficiency. The result shows the best solution for the total supply chain is 1.75 trillion, and the service level is 1,502,264.5.

МЕТОД АНАЛІТИЧНОГО МОДЕЛЮВАННЯ БЕЗВІДМОВНОСТІ БОЙОВИХ ЗАСОБІВ ЗЕНІТНИХ РАКЕТНИХ ВІЙСЬК

The article sets out a method for analytical modeling of the recoverability of anti-aircraft missile forces using the example of a self-propelled fire launcher (SOU) of the Buk anti-aircraft missile system. The main attention is paid to one of the properties of technical reliability, namely the reliability of weapons and military equipment. This is especially true of the IWT anti-aircraft missile forces, the failure to fulfill the tasks of which due to failures in operation can lead to serious consequences in operation or battle. The improved method of mathematical modeling of reliability allows taking into account the possibility of developing elements of aging and wear of MCS components in the process of expending the released resource at the operation stage, as well as taking into account the conditions of hostilities by using and developing a mathematical model in the form of a Weibull distribution in order to obtain more guaranteed indicators of reliability. It is advisable to select the final value of the mean hour of MTBF failure taking into account reaching the value of the ratio between the number of MTBF disabled due to only limited technical reliability and the amount of equipment that failed due to enemy fire action. This will increase the efficiency of the system for updating damaged MDS during hostilities, and improve the planning of production activities of repair bodies. It will also be possible to increase the overall combat effectiveness of the anti-aircraft missile regiment in the process of repelling a raid of air attack vehicles. When setting the specified ratio value, the required MTBF value can be calculated (before failure). The improved method of mathematical modeling adequately reflects the failure-free operation of the combat vehicles of the Buk anti-aircraft missile system, taking into account the conditions of hostilities. Keywords: probability of failure-free operation, failure-free simulation, continuous operation time, distribution parameters, time between failures, limited technical reliability.

ЕКОНОМІЧНИЙ АНАЛІЗ ДІЯЛЬНОСТІ ПІДПРИЄМСТВ ВЕТМЕДИЦИНИ, ЯК ЧИННИК ЗАБЕЗПЕЧЕННЯ ЕФЕКТИВНОСТІ ЇХ ФУНКЦІОНУВАННЯ

Economic reforms and changes in the ownership form pose specific tasks to veterinary medicine enterprises of Ukraine - to ensure the production of high-quality and safe products for veterinary medicine and animal husbandry, which would satisfy consumer demands based on the effectiveness of their application. In these conditions, the most important thing is to determine the available resources and the possibilities of ensuring their effective implementation, while comparing the market positions with other manufacturers regarding the competitiveness of their products. The experience of the leading enterprises of veterinary medicine of Ukraine, namely Ukrzoovetprompostach PJSC, Brovapharma LLC, Vetsintez LLC, Inter-Syntez LLC, Biopharm PJSC, etc., shows that in order to implement the strategy and policy of the enterprises, and approaches to managing available resources, including financial, raw material, energy, technical, informational, etc., are being improved. The development of business activity of enterprises should also include the improvement of personnel potential. Therefore, an assessment of its level should be important in ensuring the efficiency of enterprise activity. As the practice of the mentioned enterprises shows, the assessment of their activity is based on self-assessment data and general analysis, the results of which are used in the planning of production activities with an orientation to the market and consumer needs. Processes of analysis of enterprise activity are not limited to internal assessment, but cooperation with external organizations is also analyzed. At the same time, strengths and weaknesses are determined, as well as the effectiveness of external partnership management. Therefore, the system of analyzing the activities of enterprises should be considered as an economically justified step in the process of their development and improvement. The systematic and independent analysis is aimed at determining the compliance of enterprises with the planned measures, including strategic, as well as to determine the possibility of their implementation to achieve the set goals. And perhaps the most important benefit associated with the systematic analysis of the activities of enterprises is compliance with the requirements of current legislation, a timely assessment of the state and available production and financial advantages, and, therefore, determining the position on the market of products for veterinary medicine. Therefore, the systematic analysis of the activities of enterprises is aimed at improving their activities, developing the necessary recommendations regarding the expediency of using the results of the conducted analysis.

Mission reliability-oriented integrated scheduling optimization model by combining production planning and maintenance activities

Machine utilization and production efficiency of manufacturing systems can be effectively improved through reasonable production scheduling. Traditionally, production scheduling and maintenance planning are considered as two independent issues, but it may lead to a suboptimal solution that is unable to maximize the productivity of the manufacturing system. Therefore, a mission reliability-oriented integrated scheduling model that considers production planning and maintenance activities is proposed. Firstly, the mission reliability that takes into account product type and equipment performance is defined to characterize production rhythm. Secondly, the maintenance strategy based on machine degradation cumulative failure and stochastic failure is proposed to guarantee the mission reliability of the machine effectively. Thirdly, an integrated scheduling model is established with the goal of minimizing total operational time, and Genetic algorithm is tailored to find the best production scheduling plan. Finally, a case study and comparative study of the cylinder head manufacturing system are presented to demonstrate the effectiveness of the proposed method. Results show that the proposed method is more suitable for production practice than the previous production scheduling strategy.

Comparison of selection and combination strategies for demand forecasting methods

Abstract Paper aims In this study, effective strategies to combine and select forecasting methods are proposed. In the selection strategy, the best performing forecasting method from a pool of methods is selected based on its accuracy, whereas the combination strategies are based on the mean methods’ outputs and on the methods’ accuracy. Originality Despite the large amount of work in this area, the actual literature lacks of selection and combination strategies of forecasting methods for dealing with intermittent time series. Research method The included forecasting methods are state-of-the-art approaches applied to industrial and academics forecasting problems. Experiments were performed to evaluate the performance of the proposed strategies using a spare part data set of an industry of elevators and a data set from the M3-Competition. Main findings The results show that, in most cases, the accuracy of the demand forecasts can be improved when using the proposed selection and combination strategies. Implications for theory and practice The proposed methodology can be applied to forecasting problems, covering a variety of characteristics (e.g., intermittency, trend). The results reveal that combination strategies have potential application, perform better than state-of-the-art models, and have comparable accuracy in intermittent series. Thus, they can be employed to improve production planning activities.

Artificial Intelligence Improves Seismic-Image Reconstruction

This article, written by JPT Technology Editor Chris Carpenter, contains highlights of the open-submission paper “Artificial Intelligence for Seismic-Image Reconstruction,” by Yogendra Narayan Pandey, SPE, and Govind Chada, Prabuddha, and Tejas Karmarkar, Oracle Cloud Infrastructure. The paper was not presented at an SPE conference and has not been peer-reviewed. Seismic imaging provides vital tools•for the exploration of potential hydrocarbon reserves and subsequent production-planning activities. The acquisition of high-resolution, regularly sampled seismic data may be hindered by physical or financial constraints, which lead to undersampled, sparse seismic data. However, if seismic data are available at a higher resolution and sampled evenly throughout the region of interest, the generated 3D models of petrophysical properties could be improved. Such improvements would show potential benefits through the successive steps of reservoir modeling and production•planning. Traditional Approaches Traditional methods used to overcome the previously mentioned data-quality issues can be divided broadly into three categories. Wave-equation-based methods. These methods use physics-based•wave-propagation equations, using•velocity models•to•reconstruct missing seismic traces. Domain-transform methods. These are data-driven methods that involve transformation of data•between different domains, such as time and frequency. Prediction-error filters. These methods use a filter that learns from the known seismic data and constructs missing seismic data. Given recent advances in the field of artificial intelligence (AI), it is worth examining whether AI methods also can be useful in the task of seismic-data•reconstruction. Generative Adversarial Networks (GANs) GANs are a recent addition to the field of solution techniques. A variant of GANs, conditional generative adversarial networks, was used to test the efficacy of GANs for seismic-data reconstruction. Fig. 1 shows a schematic of a GAN model for seismic-data reconstruction. To effectively reconstruct a seismic image, a large number of 2D seismic images are fed into the GAN during the training process. A GAN model consists of two main components: Generator. This is a deep convolutional neural network (CNN) that uses random noise as an input and generates an image by expanding the input through a series of deconvolutions. As shown in Fig.•1, the generator network is fed 2D seismic images, with a portion of these masked to replicate missing traces. The generator network tries to reconstruct these•masked portions of the 2D seismic images. Discriminator. This is also a deep CNN that is shown the images reconstructed by the generator network and the original seismic images from which some parts were masked. The discriminator’s job is to distinguish between the images reconstructed by the generator from the original seismic images. As training progresses, the generator network tries to create images that the discriminator will not be able to differentiate from the original seismic images. At the same time, the discriminator’s ability to distinguish the generated images from the original images continuously improves. As a result, the generator begins producing reconstructed seismic images, which look similar to the original ones.

Моделювання розмірно-якісної структури стовбурів дуба звичайного за європейськими стандартами

Розглянуто проблеми, які виникли внаслідок набуття чинності нових стандартів на продукцію лісозаготівель. Невідповідність нормативно-інформаційної бази для таксації лісосік новим вимогам призводить до значних недоліків у плануванні виробничої діяльності лісогосподарських підприємств. Дослідження виконано на підставі дослідного матеріалу, зібраного в дубових насадженнях Придніпровського Правобережного Лісостепу на тимчасових пробних площах. Проаналізовано розподіл об'єму ділових стовбурів дуба звичайного (Quercus robur L.) на якісні категорії деревини залежно від діаметра, висоти та об'єму. Найбільш тісну лінійну залежність виявлено для абсолютних значень якісних категорій деревини від об'єму стовбура в корі. Між іншими біометричними показниками стовбура лінійна залежність відсутня або менш значуща на 5 %-му рівні. Завдяки аналізу модельовано вихід якісних категорій деревини залежно від об'єму стовбура на підставі степеневого рівняння. Пошук параметрів рівнянь виконано у MS Excel. Систематична похибка математичних моделей виходу ділової деревини виявилася близькою до нуля (1,0 %), дров та відходів – у допустимих межах (5,1 та 8,0 %), що дало змогу прийняти їх для розробки відповідних таблиць. Опрацьовані таблиці дають змогу за новими стандартами прогнозувати розподіл об'єму ділових стовбурів дуба зі стандартною похибкою 0,063-0,118 м3. Для отримання даних розподілу об'єму ділової деревини за класами розмірів, передбачених ДСТУ 1315-1-2011, розроблено в системі R алгоритм умовного розкряжування модельних дерев. Він оснований на апроксимації твірної поверхні стовбура за допомогою математичної моделі твірної A. Kozak (1988). На підставі одержаного розподілу об'єму ділової деревини за класами діаметрів досліджено його залежність від біометричних показників стовбурів. Практично для всіх розмірних категорій деревини виявлено нелінійний зв'язок. Узагальнення розмірної структури ділової деревини проведено за методикою, яка базується на дослідженні закономірностей розподілу об'єму за класами розмірів у відносних величинах. Виявлено тісну залежність відносних величин розмірної структури від діаметра модельних дерев на висоті 1,3 м. Незначна систематична похибка отриманих математичних моделей розподілу ділової деревини (-1,1-0,9 %) дала змогу прийняти їх для складання об'ємних таблиць. Розроблені за новими стандартами таблиці забезпечують прогнозування розподілу об'єму ділової деревини ділових стовбурів дуба за класами розмірів залежно від серединного діаметра лісоматеріалів без кори.

Toward Industry 4.0 With IoT: Optimizing Business Processes in an Evolving Manufacturing Factory

Research advances in the last decades have allowed the introduction of Internet of Things (IoT) concepts in several industrial application scenarios, leading to the so-called Industry 4.0 or Industrial IoT (IIoT). The Industry 4.0 has the ambition to revolutionize industry management and business processes, enhancing the productivity of manufacturing technologies through field data collection and analysis, thus creating real-time digital twins of industrial scenarios. Moreover, it is vital for companies to be as as possible and to adapt to the varying nature of the digital supply chains. This is possible by leveraging IoT in Industry 4.0 scenarios. In this paper, we describe the renovation process, guided by things2i s.r.l., a cross-disciplinary engineering-economic spin-off company of the University of Parma, which a real manufacturing industry is undergoing over consecutive phases spanning a few years. The first phase concerns the digitalization of the control quality process, specifically related to the company's production lines. The use of paper sheets containing different quality checks has been made smarter through the introduction of a digital, smart, and Web-based application, which is currently supporting operators and quality inspectors working on the supply chain through the use of smart devices. The second phase of the IIoT evolution - currently on-going - concerns both digitalization and optimization of the production planning activity, through an innovative Web-based planning tool. The changes introduced have led to significant advantages and improvement for the manufacturing company, in terms of: (i) impressive cost reduction; (ii) better products quality control; (iii) real-time detection and reaction to supply chain issues; (iv) significant reduction of the time spent in planning activity; and (v) resources employment optimization, thanks to the minimization of unproductive setup times on production lines. These two renovation phases represent a basis for possible future developments, such us the integration of sensor-based data on the operational status of production machines and the currently available warehouse supplies. In conclusion, the Industry 4.0-based on-going digitization process guided by things2i allows to continuously collect heterogeneous Human-to-Things (H2T) data, which can be used to optimize the partner manufacturing company as a whole entity.

Production Planning in the Fourth Industrial Revolution: A Literature Review

Through the decades, production planning activities have sought to balance market requirements and the optimal use of available resources in different industries. In the context of the Fourth Industrial Revolution, this study aims to disclose the purposes of production planning activities. To this end, this paper provides a literature review of the existing offer of production planning applications over the past 10 years. The authors propose a framework based on the objectives, scope and resources. The research conducted demonstrates that due to the uncertainty of the external environment, research propositions on production planning are focused on shorter planning horizons. The research also indicates that in order to face disruptions, production planning applications are mainly addressed to balance resource utilization. Ultimately, the study shows that a considerable part of innovative production planning applications have not yet been applied to real industrial cases, and moreover, they remain experimental propositions with no further use.

Implementation of Trend Moment Method for Stock Prediction as Supporting Production

Companies in each activity are accompanied by production planning activities. Determining the right amount of production will minimize the risk of loss. To assist companies in carrying out production planning activities, a system is needed that can predict the right number of products to achieve the company’s targeted profit. In this study analyzing a forecasting method is a trend moment method to analyze sales trends, then combined with the season index method. Testing using the MAPE method shows the moment trend produces an error value of 10.60%, while the combination of the trend moment method with the season index produces an error of 7.83%. The test results show that the influence of the season index can reduce the forecasting error value by 2.77%.

Composing of Scenarios Development in Strategic Planning

Abstract:
 Today, there are different points of view on the strategic planning of the production activity at enterprises and approaches to its implementation. In conditions of high uncertainty and rapid changes in the surrounding environment developing a strategy, relying only on probabilistic forecast is too risky. In an unstable environment, there are many possible options of future, which raises the need to design scenarios for key areas of development.
 In addition, it should be noted that many Russian enterprises during strategic planning of production activities "thinking scenario" has not taken root. In part, it happened due to of complication of development process and identification of scenario’s reliability. Preparation of the scenarios required significant time, while in most cases the whole system of industrial relations in the domestic enterprises built with reliance on short-term goals.
 In the above scientific paper, the authors reveal some theoretical features of the strategic planning of production activities, the approaches formed in Russia according to strategic planning, as well as the importance of developing the scenarios in the planning of activities, which directed to achieve the strategic goals of the organization. The author notes that the main meaning of development scenarios for strategic planning of industrial activity is to construct different and equally plausible options for the production development in the future. It is emphasized that the development of scenarios should be one of basic conditions for the strategic planning of industrial activity, which is capable of quickly and effectively prepare the production process and the whole enterprise for the new economic conditions.

Fundamentals of 3D modelling and resource estimation in coal mining

The prerequisite of maintaining an efficient and safe mining operation is the proper design of a mine by considering all aspects. The first step in a coal mine design is a realistic geometrical modelling of the coal seam(s). The structural features such as faults and folding must be reliably implemented in 3D seam models. Upon having a consistent seam model, the attributes such as calorific value, ash and moisture contents, volatile matter, and sulfur must be estimated in the block model. Considering the geotechnical and hydrogeological conditions, the most appropriate mine design strategy can be selected and implemented. Application of the above steps to three coal basins in Turkey are presented in this paper. The Soma-Eynez and Tuncbilek-Omerler basins are the two most important lignite resources having an on-going production and prospect for future underground mining. Comprehensive 3D coal seam modelling is carried out at both basins. As both are extensively faulted due to tectonism, it is a challenging task to realistically model their structures. On the other hand, the Karapinar basin has a considerably different geological, structural, and coal measure rock conditions in comparison to the Eynez-Omerler basin. The Karapinar basin is a relatively recently explored brown field site suitable mainly for surface mining. Coal seam(s) geometry and quality-related attributes certainly play the most important role for production planning and mining activities. The influence of the inherent characteristics of each site on the modelling and mine design strategy are also briefly discussed. This paper presents the fundamentals of coal seam modelling at various geological and structural conditions. It is believed that the methodology presented in this paper can be considered as a guiding example for a comprehensive 3D modelling and resource estimation of coal seams around the world.

Analysis of production planning activities in remanufacturing system

This article examines the problem of uncertain quantities and quality conditions of used-products obtained from the customer-stream, third-party-stream & mixed-stream on remanufacturing cycle-time under three different remanufacturing resources policies. Simulation technique is used to model a remanufacturing system with uncertain quantities and quality conditions of used-products obtained from the customer-stream, third-party-stream and mixed-stream under three different remanufacturing resource policies. Findings show that the quantities of used-products either from the customer-stream or third-party-stream affect the remanufacturing cycle-time. For used-products form the mixed-stream, the percentage of used-products from the customer-stream greatly affects the remanufacturing cycle-time. The different remanufacturing resource policies also affect the remanufacturing cycle-time. It can be established and concluded that the performance of a remanufacturing system is affected by the uncertain quantities and quality conditions of used-products.

Determination of the environmental tax on the basis of modified input-output Leontief-Ford model

The object of research is the planning of production activities, which aims to harmonize the environmental and economic criteria for the development of «nature-production». One of the most problematic places in production is environmental factor consideration, since production activity has a negative impact on the environment. The reduction of the greenhouse gases share in emissions from industrial enterprises is important particularly.Approaches to production activity modeling on the basis of inter-industry balance with environmental component are used in the course of the study.The modified ecology-economic Leontief-Ford model for the case of expanding of input-output balance taking into account the new branch that carries out the processing of greenhouse gases is analyzed in the paper. The proposed model has a feature that allows to consider the process of greenhouse gases eliminating as a separate branch of production, inextricably linked by inter-branch links with other industries.Calculations based on real data of input-output balance for 2016 are carried out. An aggregated matrix of direct costs is formed with the allocation of 8 major branches.This ensures the possibility of obtaining explicit formulas for finding or assessing the magnitude of the environmental tax, depending on the pollution of the technology. In the investigation Leontief-Ford model is redesigned to a static model of input-output balance by taking into account the emergence and functioning of a new industry – the destruction of greenhouse gases. As a result of new branch introduction the matrix of direct technological costs and the matrix of direct costs increments are obtained. The price of basic products and the cost of destroying pollutants are calculated. Compared to similar well-known models, it is possible to conclude that the proposed model provides benefits when calculating the charge for pollution. As a result, the formula for finding or estimating the value of environmental tax, depending on the contamination of the technology, is implemented. The introduction of a tax rate that takes into account the contamination of production will contribute to a more rational use of the environment and, accordingly, to reduce greenhouse gas emissions to the atmosphere.

PENGEMBANGAN MODEL PERSEDIAAN ECONOMIC MANUFACTURING QUANTITY (EMQ) DENGAN PRODUK GANDA DAN STOCHASTIC

<p><em>Pada era globalisasi seperti sekarang ini, terjadi kebebasan arus produk sehingga membuat persaingan antar perusahaan menjadi semakin ketat. Agar dapat survive, perusahaan PT. XYZ harus melakukan kegiatannya secara efektif dan efisien pada semua lini bagiannya. Salah satu lini tersebut adalah lini gudang atau persediaan. Sistem persediaan yang ada dan dijalankan oleh PT XYZ merupakan lingkungan produksi yang memproduksi lebih dari satu produk akhir dan permintaan terhadap produknya tersebut tidak pasti. Berdasarkan kondisi PT XYZ tersebut, penulis mendekati system persediaan yang ada pada PT XYZ dengan model persediaan Economic Manufacturing Quantity, produk ganda, dan stochastic. Solusi terhadap model yang dibangun, diperoleh menggunakan bantuan spreadsheet. </em></p><p><strong><em>Kata Kunci:</em></strong><em> Economic Manufacturing Quantity, Produk Ganda,Stochastic, Spreadsheet.</em></p>

Research on remanufacturing scheduling problem based on critical chain management

Remanufacturing is the recycling process of waste products as “as good as new products”, compared with materials recycling, remanufacturing represents a higher form of recycling. The typical structure of remanufacturing system consists of three parts: disassembly workshop, remanufacturing workshop and assembly workshop. However, the management of production planning and control activities can differ greatly from management activities in traditional manufacturing. Scheduling in a remanufacturing environment is more complex and the scheduler must deal with more uncertainty than in a traditional manufacturing environment. In order to properly schedule in a remanufacturing environment the schedule must be able to cope with several complicating factors which increase variability. This paper introduced and discussed seven complicating characteristics that require significant changes in production planning and control activities, in order to provide a new method for remanufacturing production scheduling system.

Simulation-based Production Planning and Execution Control for Reconfigurable Assembly Cells

In order to meet the continuously changing market conditions and achieve economy of scale, a current trend in the automotive industry is the application of modular reconfigurable assembly systems. Although they offer efficient solution to meet the customers needs, the management of these systems is often a challenging issue, as the continuous advance in the assembly technology introduces new requirements in production planning and control activities. In the paper, a novel approach is introduced that enables the faster introduction of modular assembly cells in the daily production by offering a flexible platform for evaluating the system performance considering dynamic logistics and production environment. The method is aimed at evaluating different modular cell configurations with discrete-event simulation, applying automated model building and centralized simulation model control. Besides, the simulation is linked with the production and capacity planning model of the system in order to implement a cyclic workflow to plan the production and evaluate the system performance in a proactive way, before releasing the plan to the production. The method and the implemented workflow are evaluated within a real case study from the automotive industry.