Manufacturing Execution System Research Articles

Intelligent Manufacturing for the Process Industry Driven by Industrial Artificial Intelligence

Based on the analysis of the characteristics and operation status of the process industry, as well as the development of the global intelligent manufacturing industry, a new mode of intelligent manufacturing for the process industry, namely, deep integration of industrial artificial intelligence and the Industrial Internet with the process industry, is proposed. This paper analyzes the development status of the existing three-tier structure of the process industry, which consists of the enterprise resource planning, the manufacturing execution system, and the process control system, and examines the decision-making, control, and operation management adopted by process enterprises. Based on this analysis, it then describes the meaning of an intelligent manufacturing framework and presents a vision of an intelligent optimal decision-making system based on human–machine cooperation and an intelligent autonomous control system. Finally, this paper analyzes the scientific challenges and key technologies that are crucial for the successful deployment of intelligent manufacturing in the process industry.

Manufacturing Execution System Integration through the Standardization of a Common Service Model for Cyber-Physical Production Systems

Digital transformation and artificial intelligence are creating an opportunity for innovation across all levels of industry and are transforming the world of work by enabling factories to embrace cutting edge Information Technologies (ITs) into their manufacturing processes. Manufacturing Execution Systems (MESs) are abandoning their traditional role of legacy executing middle-ware for embracing the much wider vision of functional interoperability enablers among autonomous, distributed, and collaborative Cyber-Physical Production System (CPPS). In this paper, we propose a basic methodology for universally modeling, digitalizing, and integrating services offered by a variety of isolated workcells into a single, standardized, and augmented production system. The result is a reliable, reconfigurable, and interoperable manufacturing architecture, which privileges Open Platform Communications Unified Architecture (OPC UA) and its rich possibilities for information modeling at a higher level of the common service interoperability, along with Message Queuing Telemetry Transport (MQTT) lightweight protocols at lower levels of data exchange. The proposed MES architecture has been demonstrated and validated in several use-cases at a research manufacturing laboratory of excellence for industrial testbeds.

Industrial Performance: An Evolution Incorporating Ethics in the Context of Industry 4.0

This article addresses the issue of the industrial performance model and its evolution to cope with the context of Industry 4.0. With its digitalisation, intelligent/autonomous systems and wealth of data, Industry 4.0 offers opportunities that can achieve objectives better. It also presents risks and uncertainties that question the autonomy of the systems, their interaction with humans and the use of available data. The hypothesis put forward in this work is that the efficiency–effectiveness–relevance performance triangle can no longer guarantee long-term performance under these conditions and needs to be associated with an ethical dimension that allows for the risks and uncertainties relating to Industry 4.0 to be considered. Ethics is therefore considered to extend the triangle to a tetrahedron. A brief analysis of current performance management will first show the limits of the current practice in the context of Industry 4.0. The frameworks that could overcome these limits in light of new needs are then recalled and discussed, leading to the choice of ethics, whose main definitions and use in the engineering field are also introduced. The proposed (efficiency–effectiveness–relevance–ethics tetrahedron-based methodology is illustrated through a case study related to an aeronautical supplier, regarding the consequences of the implementation of a MES (Manufacturing Execution System) in terms of product traceability and operator autonomy. The discussion and prospects finally conclude this study.

Assessing product quality from the production process logs

A real challenge for manufacturing industry is to be able to control not only the manufacturing process but also the production quality. Products that are suspected to be faulty are deviated from their nominal path in the production line and inspected more closely. The fact that some products deviate from the nominal path and others fail at some check operations can be used as an indicator of poor product quality. Based on this idea, this paper proposes a method to compute a product quality index or more exactly a penalty index taking into account both product path and production batches. The method relies on categorizing the products according to how they follow the production path and process mining techniques. The originality of the proposed index is to be built from advanced data analysis techniques enhanced by expert know-how. The quality index highlights risk of customer return, which is highly relevant information for the after sales service. The significance of the method is illustrated on a printed circuit board production line using surface mount technology at Vitesco Technologies. Data is collected from the real manufacturing execution system. The results obtained over more than 10,000 single electronic boards show that 91.7% of the products are in good compliance with respect to the requirements. For the other products, the method identifies the root causes of poor quality that may call for maintenance or reconfiguration actions.

Halal food industry certification and operation challenges and manufacturing execution system opportunities. A review study from Malaysia

The food industry has been widely regarded as an effective sector due to its contribution to the national economy, job creation, and people's welfare. Malaysia as one effective country in the food industry and leading country in Halal food brand emphasized the importance of food quality in both operation and supply chain. Despite the importance of the Halal food industry to countries' economy including Malaysia, this industry is facing multiple challenges. In addition, halal food literature still in the infant stage despite the rapid growth of this important industry. Therefore, this review study aims to identify the challenges that surrounded the Halal industry worldwide generally and Malaysian firms particularly. This study also aims to identify the potential solution to overcome Halal food challenges. The finding of this study uncovers multiple challenges surrounded the Halal food industry in operation, marketing, and certification processes. This study also suggests that the application of the manufacturing execution system can bring a new insight to overcome Halal food challenges. This study contributes to the body of knowledge by providing a clear understanding of Halal food industry operation and certification and their challenges and explains how MES can improve the efficiency of this industry.

Companies’ perception toward manufacturing execution systems

The use of information systems in manufacturing sector is very crucial to reach a high level of operational excellence and improve companies’ competitiveness. The use of such systems will definitely increase in the upcoming years, considering the digitalization strategies. Manufacturing execution systems gained a lot of attention in recent years due to showcased benefits in production management operations. Companies that adopted such systems witnessed an increase in process efficiency and enhancements with regards to cost savings and products quality. This paper seeks to analyze what makes the usage of manufacturing execution systems successful among manufacturing companies. We analyzed how the integration capabilities of such systems with other business applications and the company profile impact their usage and consequently the perceived benefits. A case study was conducted with 51 manufacturing companies and data were analyzed using partial least square structural equation modeling technique. The results confirmed the positive and significant impact of the company profile and solution integration capabilities on system usage. In addition, a ranking of solution modules importance for companies was also provided.

A design methodology for modular processes orchestration

Industry 4.0 is characterized by increased flexibility of production processes, a level of customization, a level of automation, smart manufacturing execution, and overall optimized production processes. Despite global competition, flexibility is a differentiation strategy applied by manufacturers to remain competitive. By incorporating flexibility in the manufacturing process of their products, enterprises can adapt faster to the demands. Enterprises need cost-effective, intuitive solutions to benefit from Industry 4.0 involving minimal efforts and integration costs. This study presents a new approach increasing the flexibility of manufacturing operations including robot trajectory, processing, and quality control. The results are tested in an industrial platform 4.0 installed in the laboratory. Our approach is to transform a rigid production system into an agile production system. For this, we break down the manufacturing process and reorganize it by programming core modules while maintaining the existing control structure but upgrading its programmable function to the Manufacturing Execution System Layer. Thus, the production manager can use the developed modules connected by flows to orchestrate a new production plan in a short time compared with the traditional approach.

A model-driven approach for engineering customizable MES with the application to the food and beverage industry

The Manufacturing Execution System (MES) is a process-oriented IT solution collecting and managing information from the shop floor manufacturing processes. Because of the programming and customization effort required for specific production processes, the MES implementation is not widespread in the food and beverage industry, as most food and beverage manufacturers are small- and medium-sized enterprises with limited resources to invest in MES. For engineering the MES that should be customized according to the target production processes, a model-driven approach has been presented in this paper with six phases covering the entire lifecycle of the MES engineering process. By using this approach, MES can be automatically generated and sustainably improved, which has the potential to reduce the complexity of implementation as well as the resources required for the engineering of customizable MES. Based on two use cases in the processing and packaging areas in the food and beverage industry, the feasibility and practicality of the presented approach have been proven.

The Blanket Application Model of Reference Information for Effective Manufacturing Execution System Management

In the manufacturing industry, there is a transition to multi-item production for reinforcement of competitiveness. Therefore, the hybrid manufacturing technology is increasing. Especially, many efforts in production quality improvement are made through the adoption of the Manufacturing Execution System and ERP, so it is necessary to operate MES for prompt and effective management. Therefore, the adoption of MES is necessary. MES should improve ineffective parts in production activities while managing all stages related to production of products. If there is change in the process, the changed items should be reflected to the system. However, most manufacturing execution systems are operated passively and repetitively by system administrators. This study presents a model that system administrators can comprehensively apply reference information about production related requirements on specific line’s equipment to the same equipment of other lines. To practice the model, demands of MES administrators were organized, the current system’s screen is analyzed, data for applicable reference information are classified, the screens for blanket and selective applications are designed and realized, the reference information is registered to same equipment in all the lines in case of blanket application. The reference information is registered to selected lines in case of selective application. In the results of the presented model’s test, at first it wasn’t 100% successful due to exceptional situation that the wrong data exist in the database. The validity check function for the original data that causes the exceptional situation was added, which was notified to the system administrators so that they can correct the wrong original data. The equipment reference information blanket application was implemented, and it was 100% data process accuracy. In addition, the flexible response for application to production lines is possible thanks to the division of blanket application and selective application of reference information.

Dynamic Automobile Assembly Process using IOT

In the wake of #AtmanirbharBharat and #MakeInIndia planks, there is a huge thrust to Manufacturing. This paper focuses on the Automobile Manufacturing process, enabling a customizable product, vis-a-vis a rigid Manufacturing process developed as per Industry 4.0 principles aided by IOT (Internet of Things) tools. The solution proposes to modularize entire Automobile Production/ Assembly Process, which simulates the whole process of the delivery to every customer through to the Manufacturer facilitates highly customized products based on dynamic user choices. Seamless integration of Networked Production Components is realized by building interfaces between existing ERP systems and MES (Manufacturing Execution Systems). The system adopts M3 - Modular Manufacturing Mode, via Wireless Networks for Industrial Automation - Factory Automation (WIA-FA) and Dynamic Control System, to Manufacture and Maintain Automobile Products at Scale. Proposed approach also improved Production Equipment utilization. Another aspect of this approach is flexibility of the Production/ Assembly Processes to enable high customization in product specification

Design and deployment of an analytic artefact – investigating mechanisms for integrating analytics and manufacturing execution system

ABSTRACT This paper investigates the mechanisms for integrating an analytic artefact with Manufacturing Execution System (MES), by constructing and deploying an artefact within two manufacturing sites. The findings indicate that analytic artefacts, unlike EIS or IT integrations, can be constructed based on a business problem and do not have to address specific factors such as IT-systems, process, people, or tasks. As a consequence, an analytic artefact can be built centrally and deployed across heterogeneous manufacturing sites, if they share a common data model.

Energy and maintenance management systems in the context of industry 4.0. Implementation in a real case

Industry 4.0 facilities and organization structures are used to improve energy efficiency and maintenance in industry. One of the challenges of Industry 4.0 is the urgent need to lower the consumption of energy, water and raw materials, as well as to ensure the safe and reliable running of a plant and reduce maintenance costs. The work presented herein proposes the low cost integration of Energy Management Systems (EMS) and Maintenance Management Systems (MMS) within the main management systems of a company, formed by organization appliances such as Enterprise Resource Planning (ERP), Distributed Control Systems (DCS) or Manufacturing Execution Systems (MES), The proposal has the virtue of introducing maintenance and energy saving in the company agenda. A central role in such integration is played by the generalized use of network analyzers in electric machinery; the information gained from these network analyzers is not only interesting for ascertaining energy consumption, but also for understanding the real operating conditions of the machinery, identifying premature failures or abnormal behavior. Dramatic reductions (about 50%) in energy consumption and required maintenance inspections, as well as the extension of piece replacement time, are achieved at a reasonable cost. The proposed measures have been implemented by a multinational corporation, owners of a chemical plant located in El Palmar (Murcia-Spain).

Efficient integration process of production data into Augmented Reality based maintenance of machine tools

With the increasing requirements on machine tools such as higher complexity, individuality and digitization, their maintenance becomes also more complex, which increases time consumption and demands special knowledge. The maintenance engineer can be supported in this process using the Augmented Reality (AR) technology, mobile devices and suitable production data. This requires the integration and adaptation of the maintenance documentation as well as further production systems and their data such as the CAD system, product data management (PDM) system, manufacturing execution system (MES) and CNC. For this purpose, a method is developed that allows an efficient integration process of various production data into an AR supported maintenance documentation. This includes concepts for the integration process of different production systems and data into an AR maintenance system as well as the design of the AR maintenance system architecture. Basis is the analysis of the required production and AR systems, data and processes. The aim of the method is to reduce the high expenditure of the overall planning process and the necessary expertise of the maintenance planner of the AR technology. The developed method is verified with different maintenance scenarios, production systems and data as well as machine tools and AR devices.

Evaluation of the impact of wireless communication in production via factory digital twins

This paper investigates the impact of wireless communication in manufacturing systems. By using a digital twin representation of a real production line, a production throughput evaluation is performed for various configurations considering different wireless control communication schemes over Wi-Fi, 4G LTE and 5G NR. The results show that operating the manufacturing execution system (MES) over wireless instead of Ethernet will minimally impact production, as the production throughput will not be degraded for lines containing slow stations; or will only degrade by a maximum of 0.41% during one month of continuous production in the case of fast lines involving quick stations.

An Asset Administration Shell Method for Data Exchange Between Manufacturing Software Applications

The multifaceted industrial application of cyber-physical systems (CPSs) has increased, enabling tight interactions between physical and computational elements. Industry 4.0 aims to promote industrial application of CPSs. The asset administration shell (AAS) represents the practical embodiment of the CPS, and can be obtained by integrating information and communication technologies. Most prior studies concentrated on AASs for hardware assets in the manufacturing domain; they seldom considered AASs for software applications. To fill this gap, we present a method for implementing AASs for software, i.e., a manufacturing execution system (MES) combined with an enterprise resource planning (ERP) system. This method allows runtime data exchange between an MES and ERP; this is better than the conventional file-based method. Finally, a data exchange case (a manufacturing order) is presented to validate our AAS method.

Development of an advanced MES for the simulation and optimization of industry 4.0 process

The concept of Industry 4.0 has been developed a lot from a theoretical point of view. However, the real applications on production lines remain few in number, due to the difficulties of interoperability between the different production entities and also due to the lack of a control system adapted to the expected flexibility and to the management of the data generated. This article focuses on the development and deployment of a manufacturing execution system (MES) on a production system 4.0. The development stages of the system are explained in detail. The new functionalities and the expected level of performance impose a new logic in the design of advanced systems for controlling and optimizing production. Finally, a proof of concept of an MES was developed and tested on a new technology platform 4.0.

Analysis of the information management system in the manufacturing process of cigarette enterprises using fuzzy AHP

In view of the production quality management of filter rods in the manufacturing and execution process of cigarette enterprises, this paper analyzes the necessity of implementing the manufacturing execution system (MES) in the production process of filter rods. In this paper, the filter rod quality system of cigarette enterprise based on MES is fully studied, and the constructive information management system demand analysis, cigarette quality control process, system function module design, implementation and test effect are given. This paper utilizes the Fuzzy analytic hierarchy process to find the optimal system for processing the manufacturing of cigarette. The implementation of MSE based filter rod quality information management system for a cigarette enterprise ensures the quality control in the cigarette production process. Through visualization, real-time and dynamic way, the information management of cigarette production is completed, which greatly improves the quality of cigarette enterprise manufacturing process.

A new Simulation-Based Approach in the Design of Manufacturing Systems and Real-Time Decision Making

Abstract The principles and tools made available by the Industry 4.0, smart factories, or the Internet of Things (IoT), along with the adoption of more comprehensive simulation models, can significantly help the industry to face the current, huge external and internal challenges. This paper presents a new simulation-based approach to support decision making in the design and operational management of manufacturing systems. This approach is used to evaluate different layouts and resources allocation, and help managing operations, by integrating a simulation software with real-time data collected from the production assets through an IoT platform. The developed methodology uses a digital representation of the real production system (that may be viewed as a form of a digital twin) to assess different production scenarios. A set of key performance indicators (e.g. productivity) provided by the simulation can be used by the Manufacturing Execution System (MES) to generate production schedules. The developed approach was implemented and assessed in a real case study, showing its robustness and application potential. Its extension to other industrial contexts and sectors seems, therefore, quite promising.

Manufacturing execution systems driven process analytics: A case study from individual manufacturing

The ability to trace and analyze the processes over various stages of the production value chain has become vital to generate the added value. In this context a thorough integration of the business and manufacturing processes is an essential prerequisite to facilitate the data-driven decision making which is crucial for product personalization. Implementing process analytics techniques on the critical production process data delivered by Manufacturing Execution Systems (MES) provides excessive opportunities to enhance the traceability and planning processes. To illuminate such an analytical approach, we examine in this article a use case from the individual manufacturing domain and discuss the details of the integration scenarios for MES data-driven analytics. The necessity of embedding the construction design data generated in Computer-Aided Design (CAD) systems to the proposed analytics process is particularly highlighted. The scientific and practical implications of the process analytics for different manufacturing analytics scenarios are discussed as well.

Digital twin technology as a modern approach to quality management

The concept of a digital twin and its types are discussed in this paper. The essence of the development of digital twins in the SysML language, the use of AnyLogic (simulation software) and the use of MES (Manufacturing Execution Systems) software for communication with production systems are described. The functions of neural technologies that can be integrated into a modern QMS (quality management system) are considered. The use of digital twins in the quality management system allows monitoring inconsistencies in the technological component of production and quickly eliminating them, and also offers solutions to the identified problem. Companies are now finding a competitive advantage in digital technologies, especially digital twins, whose economic benefits are undeniable. The quality management system of enterprises with high-tech industries is more and more moving into the analysis of big data and in interaction with the digital environment. Thus, it is so important to pay attention to technologies directly related to the analysis of the quality of the product and the processes of its creation. As a result of the study, a clear connection between advanced information technologies and the development of the quality management system of enterprises was revealed.