Distributed control of production systems

Recently domestic manufacturing companies have been experiencing worsening profitability and stunted growth due to the long-term economic recession and the rapid rise of developing countries such as China and Southeast Asia. These difficulties force many companies to concentrate their core competencies on new value creation and innovation in order to gain momentum for new growth. Enterprise Resource Planning (ERP) has been considered as one of viable solutions. Among the various modules in ERP, shop floor control function in the production management module is rather limited. In order to overcome this problem, Manufacturing Execution System (MES) has been used as a subsystem which has a strong information gathering power and flexibility. Both systems interact closely with each other. In particular, ERP requires fast, accurate shop floor information at MES. This paper describes how to synchronize relevant information between ERP and MES with theory of constraints (TOC). The processing time information transmitted from the MES workplace is received at the ERP workplace. In the process, the received processing time is causing information distortion in ERP, when the information gathering standard of MES is different from the ERP information interpretation standard. The Drum-Buffer-Rope theory of TOC was applied to resolve this problem, therefore, information synchronization between both systems was made. As a precondition, the standard time of the upper ERP system was rearranged according to the capacity constraints resource. As a result, standard time restructuring has affected changes in labor costs. Standard labor costs have come close to actual ones, and information synchronization of MES transmission data has improved the reliability of standard product costs, such that it enabled various company-wide restructuring actions to be much more effective.

In this paper, the system integration of an Advanced Planning and Scheduling (APS) system with Enterprise Resource Planning (ERP) and Manufacturing Execution System (MES) for a Semiconductor Backend Assembly environment is described. The company is one of the worldwide market leaders in semiconductor packaging technology. SIMTech was responsible for the implementation of the Planning & Scheduling functions through its APS application which is called Gintic Scheduling System (GSS). GSS system has been integrated with the other two key manufacturing software systems, namely ERP and MES, with the CIM framework. This paper emphasizes the system integration between the GSS and the customer's existing ERP and MES systems. The paper starts with a broader overview of the APS, ERP and MES systems with the focus on the linkage of APS with ERP and APS with MES. It then introduces the brief background information of the implementation and the integration methodology. Detailed work of the integration is laid out in the fond of integration model structure and illustrated by the system integration mechanism. Various data types that need to be integrated are also elaborated. Further discussions continue with the practical implementation issue like the required frequency of data integration and also the two approaches of data transfer. Finally the paper shares the experiences and lessons the team has learned through the implementation process and concludes the essence of the system integration work.

This paper describes the continuous application of simulation from system design to system operation including the integration of the simulation in a manufacturing execution system (MES). This is done using the example of a real-world manufacturing system, a complex flexible laser welding facility. The results of a simulation study during system design are presented and it is derived how these results strengthened the decision to implement a simulation-based MES. Some technical details of the connection between the Enterprise Resource Planning (ERP) system, the MES, and the Programmable Logic Control (PLC) are explained, as well as the usage of the MES and the simulation by the operations planners (dispatchers).

With the further integration of the informatization and industrialization, it is a key factor for enterprise to develop them by enterprise information construction. At present, with the development of computer, enterprise informatization generally has formed three layers architecture, which contains: ERP (Enterprise Resource Planning), MES (Manufacturing Execution System) and PCS (Process Control System). MES plays an irreplaceable position in the enterprise informatization. However, different needs of the design for these systems. Then, they lead system not to share information, business process effectively and work together with others. Then finally lead to "Information Island". It has made people to pay more attention to the topic, which is how to implement the exchange of information real-time and accurately between ERP, PCS and MES. So, we analyze some major exchange ways of the present information between MES and other systems in this paper. Then, we propose a flexible and configurable EAI architecture-AiOintegration (All-in-One integration), which has integrated the current methods of exchanging between system information. And AiOintegration implemented information exchange of cross-language and cross-platform between with MES and other systems.

This paper investigates the deployment of Manufacturing Execution Systems (MES) within SAP environments in manufacturing enterprises. Through an extensive literature review, it examines the critical aspects of integrating MES with SAP Enterprise Resource Planning (ERP) systems, encompassing implementation strategies, benefits, challenges, and best practices. The study underscores the significance of real-time data integration between MES and SAP for enhanced decision-making and resource utilization. It further highlights the role of MES in facilitating lean manufacturing principles and the essential nature of change management in implementation projects. The findings emphasize the necessity of aligning MES implementation with overarching business objectives and maintaining continuous performance monitoring. Practical implications for manufacturers contemplating MES implementation in SAP environments are discussed, including the importance of strategic planning, robust data integration, employee training, and ongoing system optimization. The paper concludes by identifying areas for future research, such as the impact of emerging technologies on MES implementation. Keywords: Manufacturing Execution Systems (MES), SAP, Enterprise Resource Planning (ERP),Manufacturing enterprises, System integration, Real-time data, Lean manufacturing, Change management, Implementation strategies, Performance monitoring, Data integration, Employee training, System optimization, Emerging technologies

Within the framework of Industry 4.0, the transition from stand-alone systems to an interconnected digital enterprise plays a crucial role. Increasing demands for flexibility, quality, and shorter product development cycles drive the adoption of advanced digital solutions such as product data management (PDM) systems, manufacturing execution systems (MES), advanced planning and scheduling (APS) tools, and the digital twin (DT) concept. At the same time, digitalisation trends (e.g., Smart Factory) reveal critical weaknesses of manufacturing companies, with insufficient planning and scheduling capabilities being one of the most common issues. While medium- and long-term planning is typically handled within ERP systems, operational scheduling is often still managed through inflexible spreadsheet-based solutions. APS systems are therefore gaining importance as effective tools with relatively fast return on investment, although their deployment requires alignment between ERP and MES layers as well as a thorough understanding of business and production processes. The combined implementation of PDM, APS, MES, and DT enhances decision-making, enables rapid adaptability to change, and supports the development of learning organisations. The article focuses on key principles and technologies of digital transformation with emphasis on data integration using selected tools.

In an environment of constantly growing market dynamics and associated increasing complexity of company structures and their production processes, manufacturing companies are forced to adapt to this environment. Information technology is thereby a key for manufacturing companies to regain sovereignty over their own production processes. Digital networking via their own company and as well, the overall supply chain, can only succeed if digital planning reflects reality as accurately as possible and if production control can react to deviations in real time. In essence, this leads to a development of process control towards process regulation. While long-term production and resource planning is usually mapped by Enterprise Resource Planning (ERP) systems, detailed planning, including short-term deviations and real-time data at the production level, is increasingly supported by Manufacturing Execution Systems (MES) at the production control level. However, in order to bring the underlying system concepts into line with Industry 4.0 efforts in a standardized manner, mutual functional integration within the framework of interoperable production planning and control is of crucial importance. For this purpose, studies were carried out in particular into cause-effect relationships. Thus, the overarching research objective is a valid design model to increase the controllability of production planning and control systems (PPC) in the context of Industry 4.0.

The paper proposes concept of managing territorial-production complexes (TPC) based on Continuous Intelligence (CI) principles. The developed management system fundamentally differs from traditional cybernetic models by shifting from discrete analysis to continuous monitoring and dynamic adaptation of control inputs in real-time. As a technological foundation, the authors use the DATA-CI platform implementing the method of object relations for integrating existing enterprise IT systems (Process Automation Systems, Manufacturing Execution Systems, Enterprise Resource Planning, Business Intelligence) without replacing them. The authors have tested the platform on a TPC economy model encompassing twelve production stages, demonstrating capabilities for real-time visualization of system states through mimetic diagrams, effective collection, and storage of data on all production processes. The obtained results confirm the advantages of the proposed approach, including reduced decision-making lag, improved forecasting accuracy, and comprehensive management of the TPC as a unified system. Further development prospects involve expanding the functionality of the platform and adapting the proposed concept to various types of territorial-production complexes.

With the development of information technology, information visualization and integration of ERP (Enterprise Resources Planning) and MES (Manufacturing Execution System) are becoming important tasks that many enterprises have to face. The essentiality of product information integration and information visualization was elaborated. Key technologies of the system were studied, such as database integration technologies, information parallelism, data mining and information visualization. The system of production management integration and decision information visualization was developed based on the key technologies. The results show that the production process can be controlled more precisely and the efficiency of production can be improved by this system, and it also provides supports to workshop manager’s production decision.

This paper presents a novel design of a smart and efficient Manufacturing Execution System (MES) to acquire data from the shop floor in a factory. With increasing complexities in the production process, improving industrial productivity using production information systems is a challenge for all industries in the world. Manufacturing Execution Systems (MES), since their introduction in the factory environment, are gaining popularity due to their ability to control and monitor production process using integrated data. However, employers/managers are still confronting with many complications in understanding huge information on the production process and reacting quickly based on such information. In this paper, we propose the design of NIRMAN Factory Information System (FIS)-A Smart MES to enable the control and monitoring of multiple factors of the production process like assembly line, personnel, quality control, safety, etc. NIRMAN FIS, a MES based on Android Smartphone, presents data about factory environment and factory operations on the manager's smartphone screen and helps him to react and take important decisions quickly and flexibly. Index Terms: Sectional Efficiency, Factory Efficiency, Assembly Line, Threshold Limit, Productivity, Morale, Factory Environment, Data Acquisition, Analysis, Automatic and Manual Control, Bluetooth, Arduino, Android, Remote Monitoring.

Existing solutions for analysis and optimization of manufacturing processes, such as online analysis processing or statistical calculations, have shortcomings that limit continuous process improvements. In particular, they lack means of storing and integrating the results of analysis. This makes the valuable information that can be used for process optimizations used only once and then disposed. The goal of the Advanced Manufacturing Analytics (AdMA) research project is to design an integrated platform for data-driven analysis and optimization of manufacturing processes using analytical techniques, especially data mining, in order to carry out continuous improvement of production. The achievement of this goal is based on the integration of the data related to the manufacturing processes, especially from Manufacturing Execution Systems (MES), with the other operating data, e.g. from Enterprise Resource Planning (ERP) systems. This work is based on AdMA platform described in [1] and Deep Business Process Optimization platform described in [2]. It is focused on the conceptual development of the Process Insight Repository, which is a part of the AdMA platform. The Process Insight Repository is aimed at storing the manufacturing process related data and the insights associated with it. Being part of the AdMA platform, the Process Insight Repository is oriented on storing the insights retrieved by application of data mining techniques to the data of manufacturing processes, so that the newly extracted knowledge can be stored along with the process data itself. Chapter 2 describes the conceptual schema of the Process Insight Repository. The conceptual schema defines what data must be stored in the Process Insight Repository and how different parts of this data are interconnected. Chapter 3 provides a review of technologies that can be used for the implementation of the Process Insight Repository. This includes technologies for storing manufacturing process data, free form knowledge and data mining related data. Chapter 4 describes the details of the prototype implementation of the Process Insight Repository. The result of this work is the created conceptual schema of the Process Insight Repository and a prototype implementation as a proof of concept.

Material handling systems, as an important part of different type of manufacturing processes, face the same challenges as manufacturing industries pushed nowadays forward by innovative ideas and technologies to the next level loudly announced as industry 4.0. Development of the next generation of automated manufacturing systems involves advanced approaches to material handling systems design and their close integration with the higher levels of manufacturing and production control and management, e.g. manufacturing execution systems (MES), enterprise resource planning (ERP). In the presence of increasing demands for manufacturing process optimization, the role of supervisory level of material handling systems is much more advanced today, ensuring not only data acquisition, visualization, monitoring, supervisory control, as well as synchronization with the higher control levels (FEM, ERP), but also providing functionality for supporting maintenance and decision-making processes to reduce downtimes, operations and maintenance costs. The article deals with the integration of control and maintenance functions in the hierarchical control system of a crane. The supervisory system for supporting control and proactive maintenance is prototyped at the laboratory overhead travelling crane. The article presents the control-measurement equipment and intelligent software tools implemented in the supervisory control and data acquisition (SCADA) system to aid decision-making process in proactive maintenance. The overview of the main components of the supervisory control and proactive maintenance subsystems is provided, and their respective role in control, supervision, and proactive maintenance is explained. The crane’s supervisory control includes the stereovision-based subsystem applied to identify the crane’s transportation workspace, determine the safety and time-optimal point-to-point trajectory of a payload. The proactive maintenance module consists of the human machine interface (HMI) supporting decision-making process, intelligent tools for upcoming downtime/failure prediction, and the crane's girder inspection using the metal magnetic memory technique.

Inventory control is the cornerstone of manufacturing, supply chain, and retail businesses. The precision of inventory data has a direct impact on production efficiency, order fulfillment, procurement planning, and financial reporting. Of various methods of inventory validation, cycle counting is a widely used process because it smoothes the effort of auditing the inventory across time, avoiding disrupting operations. Historically, though, the cycle count process is manual and prone to errors, particularly in companies that still use legacy Enterprise Resource Planning (ERP) systems and standalone handheld devices. This paper suggests a strong framework to automate the cycle count process by linking handheld scanning tools with ERP systems using a Microsoft .NET-based portal platform. The objective is to harmonize real-time data from ERP systems and Manufacturing Execution Systems (MES), display it for decision-making, and optimize the physical counting and data entry process. The solution specifically targets difficulties encountered in manufacturing settings where real-time inventory accuracy is difficult to achieve due to ongoing material consumption (backflushing), production variations, and incompatibilities between systems. The problem statement under discussion highlights the procedural and technological loopholes of manual inventory cycle counting. Old ERP systems are generally incompatible with new handheld devices. Organizations are stuck between either spending on expensive ERP upgrades or creating interfaces to integrate new hardware with legacy systems. The latter provides a cheaper and quicker means to attaining inventory accuracy. The solution that is being suggested involves the creation of a portal system based on Microsoft.NET and hosted on the Azure platform. The portal interacts with existing handheld devices and pulls data from ERP systems through MuleSoft APIs and MES systems through customized integrations. The portal harmonizes inventory data from both systems—both stock parts and Work-in-Progress (WIP) inventory—over 13 accounting periods. The information is displayed in color-coded indicators representing past, present, and future cycle counts, which allow analysts to make instant decisions. Once the analyst verifies the parts to cycle count, the task list is dispatched to handheld scanners used on the warehouse floor. Users perform physical counts utilizing the scanners, and the captured data is pushed back to the portal to verify. Once verified, the reconciled data is posted back to the legacy ERP system to remain the source of truth. The deployment yields tangible advantages: a 35% decrease in costs of manual cycle counting, elimination of paper-intensive processes, 320 hours less of manual data entry labor each month, and over a 40% improvement in inventory accuracy. These enhancements not only decrease carrying costs but also increase trust in inventory reports and allow for improved planning and forecasting. The paper offers a cost-effective and scalable solution to automate cycle counting by consolidating handheld technology and legacy ERP systems seamlessly. It illustrates how properly designed middleware interface can bridge the gap between old systems and new operational requirements, generating both long-term and short-term ROI. The findings strongly recommend portal-based solutions as a means of modernizing and automating inventory management procedures within manufacturing settings.

Industry 4.0, or the Fourth Industrial Revolution, is based on digitized the manufacturing process and makes use of all digital tools so its combination of various digital technologies computers, ERP software, IoT, machine learning and AI techniques, Manufacturing Execution Systems (MES), and big data analytics to create a new, fully digitized manufacturing system. The Critical Success Factors (CSFs) of MES adoption are both a quantitative and qualitative measurement. We use the case of ready-made garments to improve each of the three Overall Equipment Efficiency (OEE) factors: Availability, Performance, and Quality. In this study, we adopt real-time management of production activities on the shop floor from order receipt to finished products, then measure the improvement.

This paper studies the differential practices of change management in organizations of western origin and compares it with the best practices prevalent in Indian organizations, with special emphasis on social and cultural challenges faced in these countries. Since Enterprise Resource Planning (ERP), as part of an information and communication technology (ICT) initiative, is frequently associated with organization change and transformation in relation to its adaptation, it has been used as the context in this study. The impact of social factors and cultural challenges on change management processes and elements are compared and contrasted using multiple case studies from USA, Canada, European (Western/Eastern) and Indian organizations who have adopted ERP technologies. The conceptual framework highlights cultural and social factors that affect ERP implementation, and offers suggestions to researchers to empirically test these influences using sophisticated analytical methods and develop change strategies and practices in response to these challenges. Further, it also draws attention to the need for a contemporary, result-oriented, quantitatively measurable framework of change management at the individual and enterprise levels. It is expected that such an approach would result in better buy-in from all stakeholders in terms of increased accountability.