Journal articles on the topic 'Manufacturing resource planning Data processing'

Through building a data warehouse which is used to support manufacturing inventory analysis, according to the analysis theme, this paper extracted, purified and integrated the historical data which is accumulated by the enterprise in a long term and distributed in the various heterogeneous systems, and store them in the data warehouse fact table; through the establishment of the data cube, it generate the aggregated data with different particle size, as well as provide on-line analytical processing technology (OLAP), to provide users data query analysis with multi-angle, multi-granularity, visualization, which can solve many problems difficult to solve in the inventory analysis in traditional enterprise information processing systems.

Process planning is a task comprising a broad range of activities to design and develop an appropriate manufacturing process for producing a part. Interpretation of the part design, selection of manufacturing processes, definition of operations, operation sequences, machining datums, geometrical dimensions and tolerances are some common activities associated with the task. Manufacturing process planning can be defined as systematic determination of detailed methods by which work pieces or parts can be manufactured economically and competitively from raw material stage to final finished size. Geometrical features, dimensional sizes, tolerances, materials, and finishes, are analyzed evaluated to determine appropriate sequence of processing operations, which are based on specific, available resources viz machinery and manpower. Inputs to process planning are designing data, raw material data, resource data (machining data, tooling data, fixture data etc), quality requirement data, production type data etc. The output of a process planning is a process document which is an important document in production management. The paper mainly discusses about production planning and control of metallic manufacturing activities in an aerospace Research and Development (R&D) industry, main emphasis on manufacturing process planning. The general process planning methodology adopted in an aircraft industry is discussed. Elements and Functions of process planning, model of process planning, main mission of process planning, the interaction of processes and its process performance indices are discussed and presented. Importance of manufacturing process planning in an aerospace R&D industry is debated. Also, a case study of process planning adopted for manufacturing of a critical Aircraft system component is discussed.

<p><em>To support the bamboo processing manufacturing operations, this company uses the Enterprise Resource Planning Application System. Starting from sales operations, production, inventory to financial application systems, everything is controlled with Enterprise Resource Planning (ERP). The ERP system has actually been implemented for more than 1 year. The company wants to measure the performance of the system. Then measurements were made using the COBIT 5 Framework, with the aim of knowing between real conditions and targets (expectations). Of course there will be a gap or gap. The GAP is used as a measuring tool to improve ERP system services. Before analyzing the maturity level measurement using COBIT 5, first conduct a survey to obtain data. After getting the data, then assessing and determining the maturity level for Enterprise Resource Planning in bamboo processing manufacturing companies.</em></p><p><strong><em>Keywords:</em></strong><em> Enterprise Resource Planning; COBIT 5; </em><em>GAP</em><em>; Bamboo Processing Manufacturing; Maturity level</em></p><p><strong>Abstrak.</strong> Untuk memberikan dukungan terhadap operasional manufaktur pengolahan bambu, perusahaan ini menggunakan sistem aplikasi <em>Enterprise Resource Planning</em>. Mulai dari operasional penjualan, produksi, <em>inventory</em> sampai sistem aplikasi keuangan, semua dilakukan kontrol dengan <em>Enterprise Resource Planning</em> (ERP). Sistem ERP sebenarnya sudah diterapkan lebih dari 1 tahun. Perusahaan ingin melakukan pengukuran performansi dari sistem tersebut. Maka dilakukan pengukuran menggunakan <em>Framework COBIT</em> 5, dengan tujuan untuk mengetahui antara kondisi riil dengan target (harapan). Tentunya akan terjadi GAP atau kesenjangan. GAP tersebut dijadikan alat ukur untuk meningkatkan pelayanan sistem ERP. Sebelum melakukan analisa pengukuran tingkat kematangan menggunakan COBIT 5, terlebih dari dahulu melakukan survey untuk mendapatkan data. Setelah mendapatkan data kemudian melakukan penilaian dan penetapan tingkat kematangan (<em>maturity level</em>) untuk <em>Enterprise Resource Planning</em> pada perusahaan manufaktur pengolahan bambu.</p><p><strong>Kata kunci</strong><strong>:</strong> <em>Enterprise Resource Planning; COBIT 5; GAP; Manufaktur Pengolahan Bambu; Tingkat kematangan. </em><em></em></p>

. Variant Configuration is one of the advanced functions of the System Application and Product in data processing (SAP) business process solutions. Many enterprises, particularly from the complex production industry, can be benefited from the use of Variant Configuration. This paper demonstrates on how a product configuration is performed for a complex variable product using SAP variant configuration. The automotive pump manufacturing was as complex configurable product that involves different variants of the product. This artifact also explains on how we leverage the SAP Variant configuration functionality and achieving complex variant pump configuration with simplified solution.

The significant change in the consumption pattern of Indonesia’s modernising society––further intensified by the Indonesian Government’s plan to push towards the era of the Industrial Revolution 4.0, has fostered the need for manufacturing companies to create newly automated processes and make the transition to become a digitalised business entity. Enterprise Resource Planning is a software that enables the creation of integration and automation of business processes between various departments within a company, thus creating an effective business strategy. The data that has been acquired from research at a poultry processing company are then being mapped into the ERP software of Odoo V12.0, therefore creating new sets of re-engineered business processes. There are seven newly proposed reengineering business processes––in which only concentrate on the production and technical department within the particular company, by utilising the manufacturing and maintenance modules. The re-engineered business processes are assessed using the Technology Acceptance Model theory, to measure its usability and practicality, which generates the score of Likert’s interpretation above the accepted standard of 1340 and 1227, for both the manufacturing and maintenance modules respectively. Keywords: Business Process Reengineering, Enterprise Resource Planning, Manufacturing Process, Odoo, Technology Acceptance Model.

It is well established that the ERP systems represent transaction processing systems and are thus as such not suitable for controlling and monitoring the production in real time. Hence, a comprehensive solution proves the most efficient, ensuring connection between the process level, representing collection of actual measurements (cycle time, temperature, pressure, etc.), and business level which facilitates decision-making. The present paper focuses on the development of a comprehensive integration between the Enterprise Resource Planning (ERP) and Manufacturing Executing System (MES) system, which enables data refreshing in real time irrespective as to which the information system the change has been triggered in. Integration is performed on the basis of the Intermediate Document (IDoc) message, which enables data exchange between two databases. A new model of numbering is introduced for following cost-effectiveness of production activities. Said model allows for an efficient inspection and overview of the entire process from the design to implementation. Key words. enterprise resource planning, manufacturing executing system, intermediate document technology, integration.

The article presents an idea of a production process control system. Advanced automation and control of production processes play a key role in maintaining competitiveness. The proposed solution consists of sensor networks for measurement process parameters, production resources and equipment state. The system uses wired and wireless communication, which gives possibility to acquisition data from existing in enterprise sensors and systems as well as acquisition data from new systems and sensors used to measure all processes, starting from production preparation to the final product. The solution contains process tomography sensors based on electrical capacitance tomography, electrical impedance tomography and ultrasound tomography. The use of tomographic methods enables to manage the intelligent structure of the companies in terms of processes and products. Industrial tomography enables observation of physical and chemical phenomena without the need to penetrate inside. It will enable the optimization and auto-optimization of design processes and production. Such solutions can operate autonomously, monitor and control measurements. All sensors return to the system continuous data about state of processes in some technologically closed objects like fermenters. Process tomography can also be used to acquisition data about a flow of liquids and loose ingredients in pipeline based on transport systems. Data acquired from sensors are collected in data warehouses in order to future processing and building the knowledge base. The results of the data analysis are showed in user control panels and are used directly in the control of the production process to increase the efficiency and quality of the products. Control methods cover issues related to the processing of data obtained from various sensors located at nodes. Monitoring takes place within the scope of acquired and processed data and parameter automation.

The first purpose of this study calculated the sustainability index of economic, environmental, social criteria and the sustainability index of the whole manufacturing process conducted by CV. Indo Jati Utama (a wood processing manufacturer in Semarang that sells its products on an export scale). The second purpose of this study calculated the performance importance index of each indicator in each criterion. The last purpose of this study proposed some recommendations to increase the sustainability of the manufacturing process at CV Indo Jati Utama. This study uses the multi-grade fuzzy (MGF) method to calculate sustainability and performance importance index. This study used primary data, collected using questionnaires from five experts (General Manager, Department Head of Marketing, Department Head of Finance, Department Head of Production Planning and Inventory Control, and Department Head of Human Resource). The result of data processing indicated that the sustainability index of economic, environmental, and social and the whole manufacturing production process was 7.48, 7.60, 7.60, and 7.50 successively. Moreover, the result of data processing also indicated that the enterprise should increase the performance of five indicators to get more sustainable, namely, flexibility to change, environmental management, green image, employee compensation practices, and employee career development program.

This study aims to determine the effect of the application of System Application and Product in Data Processing on managerial performance at PT Pupuk Iskandar Muda Lhokseumawe, the use of accounting information system information technology is very important in its role in a company, Enterprise Resource Planning with its Software Application Systems and Products in Data Processing widely used by manufacturing companies that can improve the efficiency of the accounting information system that results in effective and efficient management performance, this study uses a descriptive approach, quantitative associative form, using primary data, sampling techniques used probability sampling with random sampling methods with the sample object is 55 employees of PT Pupuk Iskandar Muda. The results showed that the application of System Application and Product in Data Processing had a positive and significant effect on managerial performance at PT Pupuk Iskandar Muda, this was seen from the results of tcount> ttable (2.585> 1.67) and the coefficient of determination of 63.2% which shows that managerial performance is influenced by the application of System Applications and Products in data processing, while 36.8% is influenced by other factors outside this study.

The head of the madrasah as a top manager and leader has the obligation and responsibility to functionalize the elements of management in managing the education unit. The purpose of this study was to find out how to functionalize the elements of management in managing the thriving education unit at MAN 1 West Aceh. This study uses a descriptive qualitative analysis approach in revealing factual conditions related to ways of functionalizing the elements of management in managing a thriving education unit. The method of collecting data is through observation, interviews, and document studies on reports on madrasah activities. Data processing techniques by means of data verification, data presentation, data reduction, and drawing conclusions from research results. The technique of analyzing research data is by reflecting, interpreting and planning actions on the research results. The results show that MAN 1 West Aceh has been classified as good in terms of how to functionalize management elements in managing educational units, including: 1) functionalizing elements of human resources (man), by planning human resource needs, developing human resources and managing human resources, 2) functionalizing the financial element (money) by following the budget preparation procedures, using the budget, monitoring and reporting the budget, 3) functionalizing the elements of facilities and infrastructure (materials) by planning educational facilities and infrastructure, utilizing educational facilities and infrastructure and supervising educational facilities and infrastructure as well as 4) functionalizing the education marketing element by marketing educational service products, promoting educational services and marketing the educational service process.

In most production environments, the problem of efficiently scheduling production jobs on several machines is an important consideration when attempting to design a work plan that makes effective use of the available resources because job scheduling in manufacturing is at the crux of production planning because of its impact on revenues. This work examined the production planning and scheduling of jobs at the Nigerian Institute for Oil Palm Research (NIFOR) with the aim of developing an effective production planning method for the production of one of its products the Digester Screw Press (DSP). The material flow pattern and current manufacturing practice were observed and production data was collected on machine set up and run times. The data collected was used to estimate the actual average run times for all the machines and the total processing times for each of the three components that make up the Digester Screw Press. The Microsoft Project 2003 was used as a tool in producing an improved job schedule based on the shortest processing time rule. The technique has reduced the general processing time for the production of DSP from 157hours to 99hours. It provides low machine waiting time, high machine utilization and reduced job tardiness across the shop floor.

Since the going-global approach of Chinese enterprises has accelerated, the host country’s foreign direct investments (FDI) restrictiveness index has dramatically influenced the upgrading of China’s trade structure. This study investigates the relationship between the host country’s FDI restrictiveness index and the export sophistication of the home country. Using two-way fixed-impact models and firm-based microcosmic data, it verifies the impacts of reverse technology spillover (RTS) by the intermediary model. The empirical outcomes illustrate that the host country’s FDI restrictiveness index significantly inhibits the export sophistication of the home country. In particular, overseas equity restrictions, selection and endorsement requirements, and additional operational limitations hold more substantial influence. However, the limits on key foreign experts have promoted the export sophistication of the home country. Seemingly, host countries’ FDI restrictiveness has inhibited export sophistication in the textile industry and the processing of the resource industry but promoted the same in the mechanical and electronic industries. Likewise, the host country’s FDI restrictiveness impacts the export sophistication of the home nation through resource allocation. Manufacturing enterprises increased export sophistication by guiding resource allocation, and export trade models were changed from the previous quantitative competition to quality competition.

Abstract The probabilistic Ant Colony Optimization (ACO) approach is presented to solve the problem of designing an optimal trajectory for a mobile data acquisition platform. An ACO algorithm optimizes an objective function defined in terms of the value of the acquired data samples subject to different sets of constraints depending on the current data acquisition strategy. The analysis presented in this paper focuses on an environment monitoring system, which acquires in-situ data for precise calibration of a water quality monitoring system. The value of the sample is determined based on the concentration of the water pollutant, which in turn is obtained through processing of multi-spectral satellite imagery. Since our problem is defined in a continuous space of coordinates, and in some strategies each point is able to connect to any other point in the space, we adopted a hybrid model that involves a connection graph and also a spatial grid.

The ability to make good decisions on the deployment and use of information and communication technologies has become part of successful governance. The convergence of information, communication and multimedia technologies has created new business opportunities that will play a vital role in the economy and public life over the coming decades. On enterprises development in recent years has been dramatically influenced by the rapid development of technologies for processing and organizing them. These technologies share the role of an information integrator to support decision-making at all levels of the manufacturing enterprise. Enterprise resource planning is a key transactional application of enterprise information systems. Its main features include the ability to automate and integrate key business processes, functions and data across the enterprise.

The ability to make good decisions on the deployment and use of information and communication technologies has become part of successful governance. The convergence of information, communication and multimedia technologies has created new business opportunities that will play a vital role in the economy and public life over the coming decades. On enterprises development in recent years has been dramatically influenced by the rapid development of technologies for processing and organizing them. These technologies share the role of an information integrator to support decision-making at all levels of the manufacturing enterprise. Enterprise resource planning is a key transactional application of enterprise information systems. Its main features include the ability to automate and integrate key business processes, functions and data across the enterprise.

This paper aims at measuring the relative efficiency of the most polluting industry in terms of water pollution in Pakistan. The textile processing is country‘s leading sub sector in textile manufacturing with regard to value added production, export, employment, and foreign exchange earnings. The data envelopment analysis technique is employed to estimate the relative efficiency of decision making units that uses several inputs to produce desirable and undesirable outputs. The efficiency scores of all manufacturing units exhibit the environmental consciousness of few producers is which may be due to state regulations to control pollution but overall the situation is far from satisfactory. Effective measures and instruments are still needed to check the rising pollution levels in water resources discharged by textile processing industry of the country. JEL classification: L67, Q53 Keywords: Data Envelopment Analysis (DEA), Decision Making Unit (DMU), Relative Efficiency, Undesirable Output

This issue focuses on production planning and scheduling for production system and the related problems that have arisen in these areas in the last half century as digital computer systems developed. These problems relate to production management, production planning, shop floor control, product design and process planning. In the first stage of production planning and scheduling systems R&D, optimization is a key issue that has been widely discussed and many theories and optimization algorithms proposed. Rule-based methods are discussed as potential solutions to these problems. With rapid advances in computer and information processing technologies and performance, tremendous progress has been made in the areas of production systems such as production planning, production scheduling, advances production systems (APS), enterprise resource planning (ERP), just-in time (JIT) processes, the theory of constraint (TOC), product data management (PDM) and computer-aided design / manufacturing / engineering (CAD/CAM/CAE). This special issue addresses the latest research advances, applications, and case studies in production planning and scheduling covering such as decentralized and autonomous production systems, distributed simulation models, robust capacity planning models, wireless sensor networks for production systems and applications to automotive component and steel production. We hope that learning about these advances will enable readers to share their own experience and knowledge in technology, new developments and the potential applications of production planning and scheduling methods and solutions.

Manufacturing Execution System (MES) is widely used in enterprise production scene. But most manufacturing execution systems are expensive and mostly for the continuous production-oriented enterprises. Thus, they are hardly applied to a large number of existing discrete manufacturing enterprises. For discrete manufacturing companies, on-site processing is complex such as the planning and scheduling. This paper proposes a concept that is the use of advanced enterprise information management and designs a CIMS technology for discrete industry. The system is capable of real-time monitoring of discrete manufacturing companies in the products of the process of production and production data collection. The completion of the automatic production scheduling is achieved, providing a variety of enterprise project management module upper and greatly optimizing various production resources of the enterprise configuration. In practical applications, it has received very good results.

Manufacturing companies engaged in the system of making orders are now starting to develop with increasingly diverse needs, and the business of making agricultural and food processing machinery is no exception. UD. rekayasa Wangdi W produced the machine processing manufacturing companies engaged in the make to order system are now starting to develop rapidly along with increasingly diverse needs, and the business of making agricultural and food product processing machines is no exception. UD. Wangdi W Engineering is a Make To Order (MTO) manufacturer of processing machines which currently does not consider resource capacity and order due to date as a reference for receiving orders. Even though accepting all orders does not necessarily provide maximum benefits. To help solve these problems, a decision support system design for planning the acceptance of customer orders is carried out. The system is designed using a mathematical model that was developed and modified in linear programming. The model developed has an objective function of maximizing profits from orders received and applied in the system built. The system is designed and the Mathematical Model is processed using the branch and bound method. Based on experimentation with historical data, the results obtained are only 4 slicer and 10 spinner units with a maximum profit of Rp53,115,530.00 and order completion that does not exceed the due date. Order acceptance information is displayed in tabular form and machine scheduling information is displayed in Gantt chart format

Aiming at the requirements of CAD/CAPP data and function integration, adopted modeling based on feature, the part model design is accomplished through calling standard features in the feature database or user defined feature (UDF). The design feature model is reconstructed into a machining feature model through mapping rules. The information of machining geometric and machining properties is packaged in machining feature. CAD model does not provide all the information necessary for process planning, such as the materials information and the accuracy information. These must be provided manually. All information establishes reference of the shape feature. The machining feature, the processing method and manufacturing resources are correlated through establishing decision rules of process knowledge stored in a knowledge base, to realize the automatic generation of feature-based machining procedures and operations. A process-planning tree is constructed through matching the feature process tree with a typical process template, to realize the automatic generation of the part process route. A complete process document can be obtained by manually editing the automatically generated processing route. The feasibility of the method is verified by a prototype system developed in Pro/E environment.

This paper explores the determinants of export performance at the level of firms in respect of their characteristics and supply side constraints. The analysis is based on a survey of export-oriented firms in four major sectors. The results indicate a relationship between the better performance of foreign-owned firms to their better know-how and resources compared to the domestically owned firms. Export performance is positively affected by the level of investment in market/client oriented technologies. Lack of certification of product and process standards is the main supply side constraint adversely affecting the firms’ export performance. Facilitation measures like export processing zones, internationally recognised testing labs, and industrial clusters would be helpful in improving the export performance of firms. JEL classification: F1, L1, L6 Keywords: Trade, Exports, Firms, Performance, Manufacturing

Under the background of intelligent manufacturing, the modeling and scheduling of an intelligent manufacturing system driven by big data have attracted increasing attention from all walks of life. Deep learning can find more hidden knowledge in the process of feature extraction of the hierarchical structure and has good data adaptability in domain adaptation. From the perspective of the manufacturing system, intelligent scheduling is irreplaceable in intelligent production when the manufacturing quantity of workpieces is small or products are constantly changing. This paper expounds the outstanding advantages of deep learning in intelligent manufacturing system modeling, which provides an effective way and powerful tool for intelligent manufacturing system design, performance analysis, and running status monitoring and provides a clear direction for selecting, designing, or implementing the deep learning architecture in the field of intelligent manufacturing system modeling and scheduling. The scheduling of the intelligent manufacturing system should integrate intelligent scheduling of part processing and intelligent planning of product assembly, which is suitable for intelligent scheduling of any kind and quantity of products and resources.

Consumer electronic manufacturing (CEM) companies face a constant challenge to maintain quality standards during frequent product launches. A manufacturing test verifies product functionality and identifies manufacturing defects. Failure to complete testing can even result in product recalls. In this research, a universal automated testing system has been proposed for CEM companies to streamline their test process in reduced test cost and time. A universal hardware interface is designed for connecting commercial off-the-shelf (COTS) test equipment and unit under test (UUT). A software application, based on machine learning, is developed in LabVIEW. The test site data for around 100 test sites have been collected. The application automatically selects COTS test equipment drivers and interfaces on UUT and test measurements for test sites through a universal hardware interface. Further, it collects real-time test measurement data, performs analysis, generates reports and key performance indicators (KPIs), and provides recommendations using machine learning. It also maintains a database for historical data to improve manufacturing processes. The proposed system can be deployed standalone as well as a replacement for the test department module of enterprise resource planning (ERP) systems providing direct access to test site hardware. Finally, the system is validated through an experimental setup in a CEM company.

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.

Project Planning and Control (PPC) problems with stochastic job processing times belong to the problem class of Stochastic Resource-Constrained Multi-Project Scheduling Problems (SRCMPSP). A practical example of this problem class is the industrial domain of customer-specific assembly of complex products. PPC approaches have to compensate stochastic influences and achieve high objective fulfillment. This paper presents an efficient simulation-based optimization approach to generate Combined Priority Rules (CPRs) for determining the next job in short-term production control. The objective is to minimize project-specific objectives such as average and standard deviation of project delay or makespan. For this, we generate project-specific CPRs and evaluate the results with the Pareto dominance concept. However, generating CPRs considering stochastic influences is computationally intensive. To tackle this problem, we developed a 2-phase algorithm by first learning the algorithm with deterministic data and by generating promising starting solutions for the more computationally intensive stochastic phase. Since a good deterministic solution does not always lead to a good stochastic solution, we introduced the parameter Initial Copy Rate (ICR) to generate an initial population of copied and randomized individuals. Evaluating this approach, we conducted various computer-based experiments. Compared to Standard Priority Rules (SPRs) used in practice, the approach shows a higher objective fulfilment. The 2-phase algorithm can reduce the computation effort and increases the efficiency of generating CPRs.

Make-Up that women need to maintain their appearance and self-confidence to look more attractive for themselves and when dealing with other people. The information system is an important resource that needs to be managed by a Make-Up service provider because it has a high level of accuracy in data processing. The design of this system aims to display information on available Make-Up and Make-Up service providers including prices and locations. This system uses the PHP and MySQL programming languages. The Make-Up and Make-Up service provider system is designed using the Waterfall methodology, which starts from the planning process, needs analysis, design, and implementation in the form of coding, testing/verification and maintenance. The results of this study are a Make-Up service website that is available to make it easier for customers to choose the makeup they want, in this website, Make-Up owners can visit their services on the website and are also supported by transaction features that make it easier for customers to can place an order.

There are industry lock-in and regional lock-in phenomena in China’s manufacturing industry carbon emissions. However, the existing researches often focus on global carbon emissions, which is not adverse to finding the main problems of manufacturing industry carbon emissions. The biggest contributions of this study are the identification of the industry lock-in and regional lock-in of China’s manufacturing industry and the finding of the regional factors that affect the carbon lock-in of the manufacturing industry, which points out the direction for the low-carbon transformation of the local manufacturing industry. This paper is based on the IPCC (Intergovernmental Panel on Climate Change) carbon emissions coefficient method and energy consumption data from 2000 to 2016 to count the manufacturing industry carbon emissions of 30 provinces in China (except Hong Kong, Macao, Taiwan and Tibet). On this basis, the paper uses a spatial–temporal geographical weighted regression (GTWR) model to analysis the regional influencing factors of the high-carbon manufacturing industry. Results demonstrate that China’s high-carbon manufacturing industry mainly concentrates on the ferrous metal processing industry, non-metallic mineral manufacturing industry and other sectors. In addition, the carbon emissions of high-carbon manufacturing industries are mainly concentrated in Bohai Bay and the North China Plain. The industrial structure and economic scale are the main reasons for the regional carbon lock-in of the high-carbon manufacturing industry, and the strength of the lock-in has continued to increase. Resource endowment is a stable factor of carbon lock-in in high-carbon regions. Technological progress helps to unlock carbon, while foreign direct investment results in the enhancement of carbon regional lock-in. This study focuses on the regional factors of carbon lock-in in the manufacturing industry, hoping to provide decision support for the green development of China’s manufacturing industry.

Research is aimed at creating high-resource diamond-abrasive tools with a large-pore structure of the working layer, the use of which reduces the occurrence of grinding defects when processing materials sensitive to overheating. The formation of an open structure of the working layer ensures effective chip removal, which excludes a decrease in the сutting ability of the tool due to contamination with grinding sludge and creates favorable conditions for intensifying the processing of materials when using high-speed cutting modes. As part of the research, low-melting glass-ceramic binders for diamond-abrasive tools have been developed, which make it possible to increase the tool service life due to the prevention of diamond grains premature destruction and the creation of a large-pore open structure of the working layer. Using a set of calculated data about the main characteristics of glass compositions by factor planning means, the dependences «composition - properties» were determined and the area of optimal compositions of glass-ceramic bonds was established, which ensure sintering of a diamond-containing composite at a temperature of 550–650 °C. The efficiency of the use of alumino-silicate microspheres of technogenic origin as a structure-forming filler providing the formation of a large-pore structure is shown. The features of the chemical and phase composition of the technogenic spheres recovered from the fly ash of the Krivoy Rog TPP have been determined. It has been established that when the diamond-bearing layer of the tool is sintered in the shell of the ash spheres, crystalline new formations with high hardness (hercynite, mullite, maghemite, spinel) are formed. Using ash spheres and developed low-melting binders, which include up to 30 mass. % of glass waste, the laboratory samples of diamond-containing composites with open porosity of 45-50% were made. Studies of their microstructure and morphological features made it possible to determine the pore size (130-200 μm) and establish that during grinding, partial destruction of ash spheres occurs with the formation of additional cutting elements, which increases the tool cutting ability. The research results indicate the advisability of using the proposed approach for selection of the diamond-ceramic composite components and the modes of heat treatment of the diamond-bearing layer when creating a tool. This approach will significantly expand the possibilities of manufacturing large-pore diamond-abrasive tools with a high service life at minimal material costs and will improve the processing of parts made of difficult-to-machine materials.

The importance of a knowledge search for green innovation has been recognized, but our understanding of the influence of green search is still unclear. We used 198 Chinese manufacturing data to sort the influential mechanism of green search on green innovation based on resource-based theory, information processing theory, and transaction cost theory. We also explored the intermediate role of green control (i.e., output and behavior control) between the two dimensions of green search (i.e., search breadth and depth) and green innovation (i.e., exploratory and exploitative innovation). The results show that the diversified green information searched from outside must be controlled through the behavior process and results in improving the quality of existing green products and developing new green products. A continuous and deep search for green knowledge can achieve the results of green innovation by setting goals and monitoring processes. When Chinese manufacturing enterprises are searching for knowledge to produce green products, they must pay attention to the supervision and control of the knowledge integration process and results to ensure the effective utilization and transformation of knowledge.

In manufacturing companies, especially in SMEs, the optimization of processes in terms of resource consumption, waste minimization, and pollutant emissions is becoming increasingly important. Another important driver is digitalization and the associated increase in the volume of data. These data, from a multitude of devices and systems, offer enormous potential, which increases the need for intelligent, dynamic analysis models even in smaller companies. This article presents the results of an investigation into whether and to what extent machine learning processes can contribute to optimizing energy consumption and reducing incorrectly produced plastic parts in plastic processing SMEs. For this purpose, the machine data were recorded in a plastics-producing company for the automotive industry and analyzed with regard to the material and energy flows. Machine learning methods were used to train these data in order to uncover optimization potential. Another problem that was addressed in the project was the analysis of manufacturing processes characterized by strong non-linearities and time-invariant behavior with Big Data methods and self-learning controls. Machine learning is suitable for this if sufficient training data are available. Due to the high material throughput in the production of the SMEs’ plastic parts, these requirements for the development of suitable learning methods were met. In response to the increasing importance of current information technologies in industrial production processes, the project aimed to use these technologies for sustainable digitalization in order to reduce the industry’s environmental impact and increase efficiency.

The disruption caused by the COVID-19 pandemic has an imbalance between demand and supply in Indonesia's manufacturing industry. The products needed to handle the spread of the virus are in high order, and there is even a product shortage. Products that are not required to prevent a pandemic have stagnated so that the manufacturing industry suddenly reduces capacity. Manufacturing companies need to coordinate quickly to be able to adjust the disruption. Manufacturing companies already have an integrated information technology system that has been the primary process in Enterprise Resources Planning (ERP). Manufacturing companies make ERP their primary system, so they need to be updated and adjusted as needed. This study obtains a questionnaire from Indonesia's manufacturing industry using the google form link and distributed through social media WhatsApp, Facebook and Instagram. Data processing was carried out by using the partial least square of 285 manufacturing company respondents. The results showed that ERP sustainability was able to influence supply chain integration (internal and external). External integration has an impact on information quality, while internal integration does not affect. Supply chain integration and information quality affect increasing firm performance. Research makes a practical contribution to the industry in optimizing ERP systems in Pandemic conditions and a theoretical contribution to ERP sustainability as a mainstay in supply chain integration.

Efficient remanufacturing of end-of-life (EOL) products is crucial for environment friendly production. Disassembly is part of the remanufacturing and it is meant to obtain components and materials from end-of-life products. An essential performance objective of a disassembly process is the benefits it brings, that is the revenue brought by the retrieved parts and material, diminished by the cost of their retrieval operations. A decision must be taken to balance the disassembly production system. In this paper, a multi-agent system (MAS) is presented to optimize the remanufacturing process of EOL products. The MAS offers a synthesized information platform for various tasks, e.g. product/manufacturing information processing, disassembly sequencing, solution performance assessing, and processes scheduling. On one hand, the MAS could retrieve much information related design/manufacturing resources, by multi-level data obtaining mechanism. On the other hand, this information will make the prospective integrated environment for profitable remanufacturing system planning more feasible.

The heavy-duty truck industry has always been regarded as an “economic vane,” and as the carrier of production materials, its degree of cold and heat can better reflect the quality of the macroeconomic environment. The SAP system is currently the ERP software with the largest functions and the most sales and has been widely used by large domestic and foreign manufacturing enterprises. Because of its specific development for enterprises, it is also the most expensive ERP software in the world. This research integrates the existing information resources, takes SAP (system applications and products in data processing) system as the enterprise’s information platform, unifies the information platform into SAP system by integrating the existing information resources (financial system, logistics system, cost control system, production control system, etc.), avoids the information island phenomenon as far as possible, and finally realizes the integrated and unified enterprise information management, which is convenient for the rapid traceability of historical data, providing the best decision analysis method for managers. It is possible to eliminate all non-value-added operations in the value chain, find out the point of cost reduction and efficiency increase, comprehensively optimize the production value chain, improve production efficiency, and finally achieve the purpose of this book. The project implementation of automobile company adopts independent minicomputer system (HP server), with SAPR/3 system as the core and C/S (customer/service) architecture, so as to gradually expand the system function in the future. From the comparison before and after the launch of the SAP project, the above two indicators have increased by 1.5 times, the order fulfillment rate has increased from 30% to 45%, and the timely delivery rate has increased from 60% to 90%. Effective cost control can reduce costs, produce products with larger output and better quality at the same cost, and enable enterprises to maintain an advantage in the competition; effective cost control can also enable enterprises to develop a variety of configurations at the same cost. Products meet the individual needs of customers. The design of this article makes the company’s supply, production planning, logistics, and demand synchronized and integrated.

In past decades, manufacturing companies have paid considerable attention to using their available resources in the most efficient way to satisfy customer demands. This endeavor is supported by many Industry 4.0 methods. One of these is called MES (Manufacturing Execution System), which is applied for monitoring and controlling manufacturing by recording and processing production-related data. This article presents a possible method of implementation of a risk-adjusted production schedule in a data-rich environment. The framework is based on production datasets of multiple workshops, which is followed by statistical analysis, and its results are used in stochastic network models. The outcome of the simulation is implemented in a production scheduling model to determine how to assign the production among workshops. After collecting the necessary data, the reliability indicator-based stochastic critical path method was applied in the case study. Two cases were presented based on the importance of inventory cost and two different scheduling results were created and presented. With the objective of the least inventory cost, the production was postponed to the latest time possible, which means that workshops had more time to finish their previous work on the first day due to the small production quantity. When the cost was not relevant, the production started on the first day of each workshop, and the production was completed before the deadline. These are optimal solutions, but alternative solutions can also be performed by the decision maker based on the results. The use of the modified stochastic critical path method and its analysis shed light on the deficiency of the production, which is a merit in the continuous improvement process and the estimation of the total project time.

The textile manufacturing industry in Indonesia grew 15 percent, but total exports fell 2.87 percent to 12.84 billion dollars in 2019 compared to 2018 of 13.22 billion dollars. The TPT industry can be divided into several sectors, one of which is the apparel sector. The apparel sector also has an important GDP contribution for Indonesia. In textile product commodities, there is competition with imported quality. Textile products find it difficult to compete in the domestic market due to inferior quality to imported products, both in terms of materials, sewing, styles and finishing which are not neat and not standardized and their availability has not met market demand. In dealing with changes in the external and internal environment CV. Hadi Corp needs a business model mapping to determine the company's business conditions to be able to create breakthrough innovations for the company's business development for the domestic market. Hadi Corp needs a business model mapping to determine the company's business conditions to be able to create breakthrough innovations for the company's business development for the domestic market. The research objective is to analyze the current CV Hadi Corp Canvas Business Model, analyze the strengths, weaknesses, opportunities, and threats (SWOT) of CV Hadi Corp currently based on the 9 elements of the Canvas Business Model and Design the CV Hadi Corp Repair Canvas Business Model as an alternative planning future business strategy. Data processing uses the Canvas Business Model and SWOT and the Blue Ocean Strategy. The results showed that the Improvement of the CV Hadi COrp Canvas Business Model based on alternative strategies resulted in several targets and development for each element including: 1) Business to business customers; 2) product innovation; 3) updating the website to improve online promotion; 4) Conduct site visits to customers and customer assessment of company services through customer satisfaction surveys; 5) Investment in technology or new resources and training; 7) Customers for tool rental and design services, market surveys and manufacturing of innovative products. The target of improving each element in the canvas business model aims to expand the potential value proposition that can be offered by CV Hadi Corp. Keywords: TPT, SWOT, Business Model Canvas, Blue Ocean Strategy, CV Hadi Corp

Recent Trends and Future of Fog and Edge Computing, Services, and Enabling Technologies Cloud computing has been established as the most popular as well as suitable computing infrastructure providing on-demand, scalable and pay-as-you-go computing resources and services for the state-of-the-art ICT applications which generate a massive amount of data. Though Cloud is certainly the most fitting solution for most of the applications with respect to processing capability and storage, it may not be so for the real-time applications. The main problem with Cloud is the latency as the Cloud data centres typically are very far from the data sources as well as the data consumers. This latency is ok with the application domains such as enterprise or web applications, but not for the modern Internet of Things (IoT)-based pervasive and ubiquitous application domains such as autonomous vehicle, smart and pervasive healthcare, real-time traffic monitoring, unmanned aerial vehicles, smart building, smart city, smart manufacturing, cognitive IoT, and so on. The prerequisite for these types of application is that the latency between the data generation and consumption should be minimal. For that, the generated data need to be processed locally, instead of sending to the Cloud. This approach is known as Edge computing where the data processing is done at the network edge in the edge devices such as set-top boxes, access points, routers, switches, base stations etc. which are typically located at the edge of the network. These devices are increasingly being incorporated with significant computing and storage capacity to cater to the need for local Big Data processing. The enabling of Edge computing can be attributed to the Emerging network technologies, such as 4G and cognitive radios, high-speed wireless networks, and energy-efficient sophisticated sensors. Different Edge computing architectures are proposed (e.g., Fog computing, mobile edge computing (MEC), cloudlets, etc.). All of these enable the IoT and sensor data to be processed closer to the data sources. But, among them, Fog computing, a Cisco initiative, has attracted the most attention of people from both academia and corporate and has been emerged as a new computing-infrastructural paradigm in recent years. Though Fog computing has been proposed as a different computing architecture than Cloud, it is not meant to replace the Cloud. Rather, Fog computing extends the Cloud services to network edges for providing computation, networking, and storage services between end devices and data centres. Ideally, Fog nodes (edge devices) are supposed to pre-process the data, serve the need of the associated applications preliminarily, and forward the data to the Cloud if the data are needed to be stored and analysed further. Fog computing enhances the benefits from smart devices operational not only in network perimeter but also under cloud servers. Fog-enabled services can be deployed anywhere in the network, and with these services provisioning and management, huge potential can be visualized to enhance intelligence within computing networks to realize context-awareness, high response time, and network traffic offloading. Several possibilities of Fog computing are already established. For example, sustainable smart cities, smart grid, smart logistics, environment monitoring, video surveillance, etc. To design and implementation of Fog computing systems, various challenges concerning system design and implementation, computing and communication, system architecture and integration, application-based implementations, fault tolerance, designing efficient algorithms and protocols, availability and reliability, security and privacy, energy-efficiency and sustainability, etc. are needed to be addressed. Also, to make Fog compatible with Cloud several factors such as Fog and Cloud system integration, service collaboration between Fog and Cloud, workload balance between Fog and Cloud, and so on need to be taken care of. It is our great privilege to present before you Volume 20, Issue 2 of the Scalable Computing: Practice and Experience. We had received 20 Research Papers and out of which 14 Papers are selected for Publication. The aim of this special issue is to highlight Recent Trends and Future of Fog and Edge Computing, Services and Enabling technologies. The special issue will present new dimensions of research to researchers and industry professionals with regard to Fog Computing, Cloud Computing and Edge Computing. Sujata Dash et al. contributed a paper titled “Edge and Fog Computing in Healthcare- A Review” in which an in-depth review of fog and mist computing in the area of health care informatics is analysed, classified and discussed. The review presented in this paper is primarily focussed on three main aspects: The requirements of IoT based healthcare model and the description of services provided by fog computing to address then. The architecture of an IoT based health care system embedding fog computing layer and implementation of fog computing layer services along with performance and advantages. In addition to this, the researchers have highlighted the trade-off when allocating computational task to the level of network and also elaborated various challenges and security issues of fog and edge computing related to healthcare applications. Parminder Singh et al. in the paper titled “Triangulation Resource Provisioning for Web Applications in Cloud Computing: A Profit-Aware” proposed a novel triangulation resource provisioning (TRP) technique with a profit-aware surplus VM selection policy to ensure fair resource utilization in hourly billing cycle while giving the quality of service to end-users. The proposed technique use time series workload forecasting, CPU utilization and response time in the analysis phase. The proposed technique is tested using CloudSim simulator and R language is used to implement prediction model on ClarkNet weblog. The proposed approach is compared with two baseline approaches i.e. Cost-aware (LRM) and (ARMA). The response time, CPU utilization and predicted request are applied in the analysis and planning phase for scaling decisions. The profit-aware surplus VM selection policy used in the execution phase for select the appropriate VM for scale-down. The result shows that the proposed model for web applications provides fair utilization of resources with minimum cost, thus provides maximum profit to application provider and QoE to the end users. Akshi kumar and Abhilasha Sharma in the paper titled “Ontology driven Social Big Data Analytics for Fog enabled Sentic-Social Governance” utilized a semantic knowledge model for investigating public opinion towards adaption of fog enabled services for governance and comprehending the significance of two s-components (sentic and social) in aforesaid structure that specifically visualize fog enabled Sentic-Social Governance. The results using conventional TF-IDF (Term Frequency-Inverse Document Frequency) feature extraction are empirically compared with ontology driven TF-IDF feature extraction to find the best opinion mining model with optimal accuracy. The results concluded that implementation of ontology driven opinion mining for feature extraction in polarity classification outperforms the traditional TF-IDF method validated over baseline supervised learning algorithms with an average of 7.3% improvement in accuracy and approximately 38% reduction in features has been reported. Avinash Kaur and Pooja Gupta in the paper titled “Hybrid Balanced Task Clustering Algorithm for Scientific workflows in Cloud Computing” proposed novel hybrid balanced task clustering algorithm using the parameter of impact factor of workflows along with the structure of workflow and using this technique, tasks can be considered for clustering either vertically or horizontally based on value of impact factor. The testing of the algorithm proposed is done on Workflowsim- an extension of CloudSim and DAG model of workflow was executed. The Algorithm was tested on variables- Execution time of workflow and Performance Gain and compared with four clustering methods: Horizontal Runtime Balancing (HRB), Horizontal Clustering (HC), Horizontal Distance Balancing (HDB) and Horizontal Impact Factor Balancing (HIFB) and results stated that proposed algorithm is almost 5-10% better in makespan time of workflow depending on the workflow used. Pijush Kanti Dutta Pramanik et al. in the paper titled “Green and Sustainable High-Performance Computing with Smartphone Crowd Computing: Benefits, Enablers and Challenges” presented a comprehensive statistical survey of the various commercial CPUs, GPUs, SoCs for smartphones confirming the capability of the SCC as an alternative to HPC. An exhaustive survey is presented on the present and optimistic future of the continuous improvement and research on different aspects of smartphone battery and other alternative power sources which will allow users to use their smartphones for SCC without worrying about the battery running out. Dhanapal and P. Nithyanandam in the paper titled “The Slow HTTP Distributed Denial of Service (DDOS) Attack Detection in Cloud” proposed a novel method to detect slow HTTP DDoS attacks in cloud to overcome the issue of consuming all available server resources and making it unavailable to the real users. The proposed method is implemented using OpenStack cloud platform with slowHTTPTest tool. The results stated that proposed technique detects the attack in efficient manner. Mandeep Kaur and Rajni Mohana in the paper titled “Static Load Balancing Technique for Geographically partitioned Public Cloud” proposed a novel approach focused upon load balancing in the partitioned public cloud by combining centralized and decentralized approaches, assuming the presence of fog layer. A load balancer entity is used for decentralized load balancing at partitions and a controller entity is used for centralized level to balance the overall load at various partitions. Results are compared with First Come First Serve (FCFS) and Shortest Job First (SJF) algorithms. In this work, the researchers compared the Waiting Time, Finish Time and Actual Run Time of tasks using these algorithms. To reduce the number of unhandled jobs, a new load state is introduced which checks load beyond conventional load states. Major objective of this approach is to reduce the need of runtime virtual machine migration and to reduce the wastage of resources, which may be occurring due to predefined values of threshold. Mukta and Neeraj Gupta in the paper titled “Analytical Available Bandwidth Estimation in Wireless Ad-Hoc Networks considering Mobility in 3-Dimensional Space” proposes an analytical approach named Analytical Available Bandwidth Estimation Including Mobility (AABWM) to estimate ABW on a link. The major contributions of the proposed work are: i) it uses mathematical models based on renewal theory to calculate the collision probability of data packets which makes the process simple and accurate, ii) consideration of mobility under 3-D space to predict the link failure and provides an accurate admission control. To test the proposed technique, the researcher used NS-2 simulator to compare the proposed technique i.e. AABWM with AODV, ABE, IAB and IBEM on throughput, Packet loss ratio and Data delivery. Results stated that AABWM performs better as compared to other approaches. R.Sridharan and S. Domnic in the paper titled “Placement Strategy for Intercommunicating Tasks of an Elastic Request in Fog-Cloud Environment” proposed a novel heuristic IcAPER,(Inter-communication Aware Placement for Elastic Requests) algorithm. The proposed algorithm uses the network neighborhood machine for placement, once current resource is fully utilized by the application. The performance IcAPER algorithm is compared with First Come First Serve (FCFS), Random and First Fit Decreasing (FFD) algorithms for the parameters (a) resource utilization (b) resource fragmentation and (c) Number of requests having intercommunicating tasks placed on to same PM using CloudSim simulator. Simulation results shows IcAPER maps 34% more tasks on to the same PM and also increase the resource utilization by 13% while decreasing the resource fragmentation by 37.8% when compared to other algorithms. Velliangiri S. et al. in the paper titled “Trust factor based key distribution protocol in Hybrid Cloud Environment” proposed a novel security protocol comprising of two stages: first stage, Group Creation using the trust factor and develop key distribution security protocol. It performs the communication process among the virtual machine communication nodes. Creating several groups based on the cluster and trust factors methods. The second stage, the ECC (Elliptic Curve Cryptography) based distribution security protocol is developed. The performance of the Trust Factor Based Key Distribution protocol is compared with the existing ECC and Diffie Hellman key exchange technique. The results state that the proposed security protocol has more secure communication and better resource utilization than the ECC and Diffie Hellman key exchange technique in the Hybrid cloud. Vivek kumar prasad et al. in the paper titled “Influence of Monitoring: Fog and Edge Computing” discussed various techniques involved for monitoring for edge and fog computing and its advantages in addition to a case study based on Healthcare monitoring system. Avinash Kaur et al. elaborated a comprehensive view of existing data placement schemes proposed in literature for cloud computing. Further, it classified data placement schemes based on their assess capabilities and objectives and in addition to this comparison of data placement schemes. Parminder Singh et al. presented a comprehensive review of Auto-Scaling techniques of web applications in cloud computing. The complete taxonomy of the reviewed articles is done on varied parameters like auto-scaling, approach, resources, monitoring tool, experiment, workload and metric, etc. Simar Preet Singh et al. in the paper titled “Dynamic Task Scheduling using Balanced VM Allocation Policy for Fog Computing Platform” proposed a novel scheme to improve the user contentment by improving the cost to operation length ratio, reducing the customer churn, and boosting the operational revenue. The proposed scheme is learnt to reduce the queue size by effectively allocating the resources, which resulted in the form of quicker completion of user workflows. The proposed method results are evaluated against the state-of-the-art scene with non-power aware based task scheduling mechanism. The results were analyzed using parameters-- energy, SLA infringement and workflow execution delay. The performance of the proposed schema was analyzed in various experiments particularly designed to analyze various aspects for workflow processing on given fog resources. The LRR (35.85 kWh) model has been found most efficient on the basis of average energy consumption in comparison to the LR (34.86 kWh), THR (41.97 kWh), MAD (45.73 kWh) and IQR (47.87 kWh). The LRR model has been also observed as the leader when compared on the basis of number of VM migrations. The LRR (2520 VMs) has been observed as best contender on the basis of mean of number of VM migrations in comparison with LR (2555 VMs), THR (4769 VMs), MAD (5138 VMs) and IQR (5352 VMs).

The centralized planning and control that has defined the traditional information processing structure of manufacturing systems is no longer suited to the current rapidly changing manufacturing environment. For efficient use of manufacturing resources and increased flexibility, it is necessary to migrate to a distributed information processing system in which individual entities can work cooperatively towards overall system goals. The next generation of manufacturing systems requires such an information technology framework to integrate the system components and activities into a larger collaborative enterprise. This paper describes a multi-agent approach to concurrent design, manufacturability analysis, process planning, routing and scheduling. A heterogeneous multi-agent concurrent engineering system consisting of multiple feature-based design sub-systems, multiple simulated shop-floor resource groups, a supervisory control interface and the coordination mechanisms for multi-agent cooperation, has been developed. The architecture of this distributed system and the associated implementation issues are discussed.

Each factory and manufacturing plant needs a flexible and reliable in-plant resource supply to serve production processes efficiently. Manufacturing systems are composed of several numbers of elements, workstations, machines and logistics resources. Production line is a complex system because of the complicated manufacturing process, multiple types, high machining difficulty and many special processes in it. In the Industry 4.0 based on smart manufacturing, it is essential to support the processes with intelligent sensor networks. In this article, we give a brief overview about sensors often used in manufacturing processes. Sensor networks generate a massive and increasing amount of data that needs to be processed. Computationally intensive algorithms are used for the data processing (image, voice and signal processing, different classification functions, numeric optimization routines). Finally, we discuss how GPGPU can improve the real-time processing of data generated by intelligent sensor networks.

The sustainability of manufacturing processes lies in industrial planning and productive activity. Industrial plants are characterized by the management of resource (inputs and outputs), processing and conversion processes, which usually are organized in a linear system. Good planning will optimize the manufacturing and promoting the quality of the industrial system. Cradle to Cradle is a new paradigm for engineering and sustainable manufacturing that integrates projects (industrial parks, manufacturing plants, systems and products) in a framework consistent with the environment, adapted to the society and technology and economically viable. To carry it out, we implement this paradigm in the MGE2 (Genomic Model of Eco-innovation and Eco-design), as a methodology for designing and developing products and manufacturing systems with an approach from the cradle to cradle.

A review of sales-order-processing (SOP) characteristics in assemble-to-order and make-to-stock companies is described. A logical model of three types of exception and their impacts is developed. This model is used to identify SOP requirements that need to be satisfied by next-generation workflow systems. With reference to these requirements deficiencies in current based workflow system provision based on enterprise resource planning are discussed.

Nowadays, the development of information technology is very fast, which allows many companies to receive the latest information technology to support the smooth running of the company's business. CV. Dewi Bulan is a small and mediu enterprise (UKM) that produces incense stick. The problems that faced by CV. Dewi Bulan is an inefficient business process, its business activities are still manually recorded, documents related to the sale, production and purchase of raw materials are still handwritten on a form in the company and the bookkeeping is done once a month. These documents cannot be accessed in real-time. This problem causes delays in processing of customer orders. The solution to overcome this problem above is to implement Enterprise Resource Planning, where in practice, ERP can automate business practices and company business procedures. ERP implementation uses a technology that is using Odoo version 11.0. This research method consists of six stages of the research process, namely; literature study, data collection, data processing, application modeling, system testing >and implementation, also conclusions and suggestions as well. The final stage in this research is to conduct a survey with the UAT questionnaire and a Likert scale to assess the satisfaction level of Odoo application users. The results of the questionnaire were dominated by the assessment of "Satisfied", this indicate that the business improvement process is made were acceptable and applied in CV. Dewi Bulan. Keywords: Business Process, Enterprise Resource Planning, Odoo, Likert Scale, UAT.

Enterprise Resource Planning, a collective integrated approach for all business solutions, has been broadly accepted across various industries since 1990 as the upcoming generation of Manufacturing Business System and Manufacturing Resource Planning software. ERP can be taken as to be “the cost of entry for running and growing a business” (Kumar and van Hillegersberg, 2000). An ERP is an information system, which seamlessly integrated and configured for planning, execution and managing all the resources and their maximum use in the enterprise, and streamlines and incorporates the business threads within and across the functional or technical boundaries in the enterprises. With the use of such information system, an organization can automate its elementary business requirements by reducing the complexity and cost of the related integrations for its components. Enterprise may also apply business process reengineering for optimum utilization of its ERP system, and finally output as growth in business can be recorded. Thus, ERP Security plays major role in protecting an organization business data and their employee’s and customer information as well. Study of Access Control Model of ERP Security is very important to keep the enterprise IT environment safe and secure. This paper focuses on the Risk of Fraudulent behavior of user roles across in terms of usage of ERP system. The case study used the information and data based on questionnaire and various inputs from industry experts.

This study aims to determine the effect of supply chain management and the implementation of enterprise resource planning on organizational performance. The population and sample used in this study was employees of PT. Semen Padang is involved in the supply chain management process and runs an enterprise resource planning system. Data was collected through distributing questionnaires and data processing was carried out through SPSS 16.0 software. The results of this study indicate that supply chain management has a significant positive effect on organizational performance. The results of this study indicate that the implementation of enterprise resource planning on organizational performance has a significant positive effect on organizational performance.Keywords: Enterprise resource planning, supply chain management, organizational performance

There are still some companies that do not apply ERP with company/organizational processing. ERP implementation is very important for companies, therefore it is necessary to find the right vendor to be applied to the company. So this research is needed to find out which vendors are most widely used in global business. The method used in this research is to find data in the literature and related journals. This research results in an ERP vendor that relatively dominates the market is SAP.

Digital manufacturing has been considered, over the last decade, as a highly promising set of technologies for reducing product development times and cost as well as for addressing the need for customization, increased product quality, and faster response to the market. This paper describes the evolution of information technology systems in manufacturing, outlining their characteristics and the challenges to be addressed in the future. Together with the digital manufacturing and factory concepts, the technologies considered in this paper include computer-aided design, engineering, process planning and manufacturing, product data and life-cycle management, simulation and virtual reality, automation, process control, shopfloor scheduling, decision support, decision making, manufacturing resource planning, enterprise resource planning, logistics, supply chain management, and e-commerce systems. These technologies are discussed in the context of the digital factory and manufacturing concepts.

This paper proposes a robust method of capacity requirements planning (CRP) that can generate a stable load plan against dynamic changes in a manufacturing environment. In our study, robustness refers to the degree of stability in the load plan for the occurrence of unexpected events. The purpose of the proposed method is to determine the processing periods of operation orders with the aim of minimizing the probability that the resource requirement of each operation order will exceed the capacity of corresponding resources. Through numerical experiments, we demonstrate the effectiveness of the proposed CRP method in terms of its robustness.

Based on the data of provincial input-output model and the carbon footprint model, the analysis is focused on provincial carbon footprint and the space transfer of carbon emissions. The results have shown that: (1) There are significant differences of provincial total carbon footprint amounts: resource-rich provinces have high total carbon footprint amounts, followed by processing and manufacturing provinces and municipalities; Regions with high energy efficiency have low carbon footprint amounts, so does southwestern region where economic and industrial development level is relatively low. (2) The provincial differences of carbon footprint per capita are related to demand structure: the amounts of carbon footprint are high in provinces with higher demand of consumption and investment, especially those provinces with strong demand for construction and processing industries. The amounts of carbon footprint are low in provinces which are non-resource-based, have limited investment and construction, and its economic structure is not dominated by processing and manufacturing. (3) Interprovincial trades have a significant impact on carbon footprint and carbon emissions. Provinces with well developed infrastructure have net CO2 emissions flow-in that are directly induced by high energy consumption products; southwestern region, where processing and manufacturing industry is relatively less-developed, has main CO2 emission flow-in, which are induced by the demand of processing and manufacturing industries; resource-intensive provinces and provinces with well-developed processing and manufacturing industries have net CO2 emission flow-out, which are induced by interprovincial trades.

Some previous studies assess the key to successful ERP implementation is the success of the organization. The purpose of this study is to analyze and re-evaluate the factors that influence the success of ERP implementation in an organizational perspective. The design of this study used descriptive quantitative methods. The data used are primary data with questionnaires as data collection. Technical analysis of data using multiple linear regression. A total of 60 respondents were obtained from service, manufacturing and banking companies in the city of Surabaya. Based on the results of the regression analysis of organizational culture and organizational leadership has a positive and significant relationship to the success of ERP implementation. While the support of top management and organizational environment does not have a significant relationship to the success of ERP implementation. Keywords : ERP Implementation; Organization; Leadership.