Modular Manufacturing Systems Research Articles

Developing a Modular Continuous Drug Product Manufacturing System with Real Time Quality Assurance for Producing Pharmaceutical Mini-Tablets

The pharmaceutical industry has shown keen interest in developing small-scale modular manufacturing systems for producing medicinal products. These systems offer agile and flexible manufacturing, and are well-suited for use in situations requiring rapid production of drugs such as pandemics and humanitarian disasters. The creation of such systems requires the development of modular facilities for making solid oral drug products. In recent years, however, the development of such facilities has seen limited progress. This study presents a development of a prototype modular system that uses drop on demand (DoD) printing to produce personalized solid oral drug products. The system's operation is demonstrated for manufacturing mini-tablets, a category of pediatric drug products, in continuous and semi-batch modes. In this process, the DoD printer is used to generate molten formulation drops that are solidified into mini-tablets. These dosages are then extracted, washed and dried in a continuous filtration and drying unit which is integrated with the printer. Process monitoring tools are also incorporated in the system to track the critical quality attributes of the product and the critical process parameters of the manufacturing operation in real time. Future areas of innovation are also proposed to improve this prototype unit and to enable the development of advanced drug manufacturing systems based on this platform.

Technology Modules Providing Solutions for Agile Manufacturing

In this paper, we address the most pressing challenges faced by the manufacturing sector, particularly the manufacturing of small and medium-sized enterprises (SMEs), where the transition towards high-mix low-volume production and the availability of cost-effective solutions are crucial. To overcome these challenges, this paper presents 14 innovative solutions that can be utilized to support the introduction of agile manufacturing processes in SMEs. These solutions encompass a wide range of key technologies, including reconfigurable fixtures, low-cost automation for printed circuit board (PCB) assembly, computer-vision-based control, wireless sensor networks (WSNs) simulations, predictive maintenance based on Internet of Things (IoT), virtualization for operator training, intuitive robot programming using virtual reality (VR), autonomous trajectory generation, programming by demonstration for force-based tasks, on-line task allocation in human–robot collaboration (HRC), projector-based graphical user interface (GUI) for HRC, human safety in collaborative work cells, and integration of automated ground vehicles for intralogistics. All of these solutions were designed with the purpose of increasing agility in the manufacturing sector. They are designed to enable flexible and modular manufacturing systems that are easy to integrate and use while remaining cost-effective for SMEs. As such, they have a high potential to be implemented in the manufacturing industry. They can be used as standalone modules or combined to solve a more complicated task, and contribute to enhancing the agility, efficiency, and competitiveness of manufacturing companies. With their application tested in industrially relevant environments, the proposed solutions strive to ensure practical implementation and real-world impact. While this paper presents these solutions and gives an overview of their methodologies and evaluations, it does not go into their details. It provides summaries of comprehensive and multifaceted solutions to tackle the evolving needs and demands of the manufacturing sector, empowering SMEs to thrive in a dynamic and competitive market landscape.

Towards automated risk assessments for modular manufacturing systems

Abstract Manufacturing systems based on Industry 4.0 concepts provide a greater availability of data and have modular characteristics enabling frequent changes. This raises the need for new security engineering concepts that cover the increasing complexity and frequency of mandatory security risk assessments. In contrast, the current standardization landscape used for the assessment of these systems only offers abstract, static, manual, and resource-intensive procedures. Therefore, this work proposes a method that further specifies the IEC 62443 aiming to automate the security risk assessments in such a way that manual efforts can be reduced and a consistent quality can be achieved. The methodology is presented using network segmentation as a guiding example and consists of four main steps: Information collection based on a process analysis, information formalisation with a semi-formal model, information usage applying first order logic to extract expert knowledge, and information access using the concept of the digital twin. In addition, the applicability of the IEC 62443 standard to the risk assessment of modular manufacturing systems is evaluated.

Joint decision-making of virtual module formation and scheduling considering queuing time

Formation and scheduling are the most important decisions in the virtual modular manufacturing system; however, the global performance optimization of the system may be sacrificed via the superposition of two independent decision-making results. The joint decision of formation and scheduling is very important for system design. Complex and discrete manufacturing enterprises such as shipbuilding and aerospace often comprise multiple tasks, processes, and parallel machines, resulting in complex routes. The queuing time of parts in front of machines may account for 90% of the production cycle time. This study established a weighted allocation model of a formation-scheduling joint decision problem considering queuing time in system. To solve this nondeterministic polynomial (NP) problem, an adaptive differential evolution-simulated annealing (ADE-SA) algorithm is proposed. Compared with the standard differential evolution (DE) algorithm, the adaptive mutation factor overcomes the disadvantage that the scale of DE’s differential vector is difficult to control. The selection strategy of the SA algorithm compensates for the deficiency that DE’s greedy strategy may fall into a local optimal solution. The comparison results of four algorithms of a series of random examples demonstrate that the overall performance of ADE-SA is superior to the genetic algorithm, and average iteration, maximum completion time, and move time are 24%, 11%, and 7% lower than the average of other three algorithms, respectively. The method can generate the joint decision-making scheme with better overall performance, and effectively identify production bottlenecks through quantitative analysis of queuing time.

A spatial superstructure approach to the optimal design of modular processes and supply chains

Modularity is a design principle that aims to provide flexibility for spatio-temporal assembly/disassembly and reconfiguration of systems. This design principle can be applied to multiscale (hierarchical) manufacturing systems that connect units, processes, facilities, and entire supply chains. Designing modular systems is challenging because of the need to capture spatial interdependencies that arise between system components due to product exchange/transport between components and due to product transformation in such components. In this work, we propose an optimization framework to facilitate the design of modular manufacturing systems. Central to our approach is the concept of a spatial superstructure, which is a graph that captures all possible system configurations and interdependencies between components. The spatial superstructure is a generalization of the notion of a superstructure and of a p-graph used in process design, in that it encodes spatial (geographical) context of the system components. We show that this generalization facilitates the simultaneous design and analysis of processes, facilities, and of supply chains. Our framework aims to select the system topology from the spatial superstructure that minimizes design cost and that maximizes design modularity. We show that this design problem can be cast as a mixed-integer, multi-objective optimization formulation. We demonstrate these capabilities using a case study arising in the design of a plastic waste upcycling supply chain.

Defining the Number of Mobile Robotic Systems Needed for Reconfiguration of Modular Manufacturing Systems via Simulation

The European vision of the Factory of the Future is based on increasing competition and sustainability by transformation from cost orientation to high-adding value with technical and organisational innovations. One of the expected outcomes is an increase in modularisation, i.e., the reconfigurability of the technical system in manufacturing conditions. Modular manufacturing systems (MMS), will consist of modular platforms (MP) that are capable of rapid rebuilding, and reconfiguration performed by adding or removing a module by Mobile Robotic Systems (MRS). In the conditions of MMS, to make the most efficient use of reconfiguration MRS capacities, it is necessary to know the optimal ratio of these MRS to the number of modular platforms (MP) used in MMS, which does not exist today. This ratio will help industrial companies that are deploying MMS-based solutions to plan the number of MRSs needed to reconfigure deployed systems. As a method of determining this optimal ratio, an experimental approach via simulation was chosen, using data from custom MRS and MP prototypes with testing different layouts of modular platforms with the view of warehouse layout, manufacturing island, manufacturing island power supply, and MRS. Based on the results, it can be determined that the MP-MRS limit ratio is 2:1, where the further increase in MRS has only a minimal impact on the reconfiguration period. With the reduction of MP transferred to one MRS, there is a gradual decrease in the time required for reconfiguration. When the ratio of 1:1 is attained, the time required for reconfiguration lowers, but not as dramatically as in bigger ratios.

Multi-Objective Optimization of a Cost-Effective Modular Reconfigurable Manufacturing System: An Integration of Product Quality and Vehicle Routing Problem

Multi-Objective Optimization of a Cost-Effective Modular Reconfigurable Manufacturing System: An Integration of Product Quality and Vehicle Routing Problem

Digital Twin and Reinforcement Learning-Based Resilient Production Control for Micro Smart Factory

To achieve efficient personalized production at an affordable cost, a modular manufacturing system (MMS) can be utilized. MMS enables restructuring of its configuration to accommodate product changes and is thus an efficient solution to reduce the costs involved in personalized production. A micro smart factory (MSF) is an MMS with heterogeneous production processes to enable personalized production. Similar to MMS, MSF also enables the restructuring of production configuration; additionally, it comprises cyber-physical production systems (CPPSs) that help achieve resilience. However, MSFs need to overcome performance hurdles with respect to production control. Therefore, this paper proposes a digital twin (DT) and reinforcement learning (RL)-based production control method. This method replaces the existing dispatching rule in the type and instance phases of the MSF. In this method, the RL policy network is learned and evaluated by coordination between DT and RL. The DT provides virtual event logs that include states, actions, and rewards to support learning. These virtual event logs are returned based on vertical integration with the MSF. As a result, the proposed method provides a resilient solution to the CPPS architectural framework and achieves appropriate actions to the dynamic situation of MSF. Additionally, applying DT with RL helps decide what-next/where-next in the production cycle. Moreover, the proposed concept can be extended to various manufacturing domains because the priority rule concept is frequently applied.

Modular Design Method for Reconfigurable Manufacturing Systems

Reconfigurable manufacturing systems (RMS) have the potential to reduce investments, time-to-market, and cost of variety in increasingly complex markets. However, tools to support the transition in industry are lacking. One enabler of RMS is modularity, however few methods support the design of modular manufacturing systems, and even fewer modular RMS. This research proposes an adaption of the Modular Function Deployment method to address this issue, and also identifies a number of additional module drivers which are relevant to support the modularization process of RMS.

Layout design considering movement planning in dynamically reconfigurable modular manufacturing systems

Layout design considering movement planning in dynamically reconfigurable modular manufacturing systems

Process Intensification through Directly Coupled Autothermal Operation of Chemical Reactors

Summary Autothermal operation of a chemical reactor involves coupling exothermic and endothermic chemical reactions for the purpose of thermal management without resorting to external energy sinks or sources. Often this is accomplished through regenerative or recuperative heat exchange between spatially or temporally separated exothermic and endothermic reactions. However, it is also possible to directly couple these reactions simultaneously within the same reactor volume, eliminating the heat-transfer bottleneck that characterizes much of chemical manufacture. It is not widely recognized that directly coupled autothermal operation allows dramatic process intensification. This perspective defines autothermal operation and contrasts it with conventional heat transfer for thermal management of chemical processes. The intensification and cost savings that can be achieved are quantified, and the implications to modular chemical process intensification are presented. Guidelines are proposed for designing directly coupled autothermal processes. Diverse examples are presented. Several challenges to expanding the field are critically discussed.

Securing IT/OT Links for Low Power IIoT Devices: Design Considerations for Industry 4.0

Manufacturing is facing a host of new security challenges due to the convergence of information technology (IT) and operational technology (OT) in the industry. This article addresses the challenges that arise due to the use of low power Industrial Internet of Things (IIoT) devices in modular manufacturing systems of Industry 4.0. First, we analyze security challenges concerning the manufacturing execution system (MES) and programmable logic controllers (PLC) in IIoT through a selective literature review. Second, we present an exploratory case study to determine a protocol for cryptographic key management and key exchange suitable for the Smart Production Lab of Aalborg University (a learning cyber-physical factory). Finally, we combine the findings of the case study with a quality function deployment (QFD) method to determine design requirements for Industry 4.0. We identify specific requirements from both the high-level domain of factory capabilities and the low-level domain of cryptography and translate requirements between these domains using a QFD analysis. The recommendations for designing a secure smart factory focus on how security can be implemented for low power and low-cost IIoT devices. Even though there have been a few studies on securing IT to OT data exchange, we conclude that the field is not yet in a state where it can be applied in practice with confidence.

Integer Linear Programming Model and Algorithm to Integrate Heuristics Scheduling EDD, Inventory Control and Distribution Problems in a Modular Production System

In this paper, a two-stage algorithm developed for the cutting sequencing problem in a modular manufacturing system. This system has a level of flexibility depends on the cutting stage of raw material. This paper focuses primarily on the work station. In the first stage of the algorithm, an integer linear programming model is used to determine the number of hardboards that will be cut. The model was tested with two different objective function is to minimize waste and to minimize the number of hardboards used. In the second stage, a heuristic developed a scheduling pattern of cutting, where the due date and the number of requests demand a consideration. This algorithm is further implemented in a furniture manufacturer that operates using the make-to-order basis.

A novel optimization method for modular facilities layout problem considering flexible processes

With the growth of personalized customer requirements, modular manufacturing system is commonly recognized as the key to response to diverse production requirement in mass customization. However, there is lack of research on the optimization problem for modular facilities layout planning. Thus, the aim of this paper is to develop a methodology for the reconfigurable modular facilities layout problem with alternative process routings and an integrated mathematical model is proposed to improve production flexibility and minimize material handling costs. An improved heuristic algorithm is developed and numerical examples are carried out to demonstrate the effectiveness of the methods.

Using queuing theory and simulated annealing to design the facility layout in an AGV-based modular manufacturing system

An automated guided vehicle-based flow production system is used for manufacturing prefabricated bathroom units. One unit can occupy a space of more than 10 m2. Due to large time deviations in sequential processes, queues are formed and greater plant space is needed. Reducing work-in-progress helps to save plant space but renders manufacture less efficient. The research explores better workstation arrangements. An open queuing network (OQN) model was used to approximate the flow production system. Since the problem of workstation arrangement is a combinatorial optimisation problem, simulated annealing (SA) was applied to search for a good solution. The combination of an OQN model and SA provides a powerful tool to solve the facility layout problem for a stochastic flow production system. The experimental results show that the proposed approach has the potential to guide industrial layout design and practice.

Reconfigurable and transportable container-integrated production system

In this paper, the concept and the prototype realization of a novel reconfigurable small-footprint manufacturing system in a transportable container is presented. The containerized format enables transportation of the system to provide on-site manufacturing, enabling the benefits of localized service delivery without duplication of equipment at multiple locations. Three industrial product use cases with varying manufacturing and performance requirements were analysed. All of the use cases demanded highly customized products with high quality in low production volumes. Based on their requirements, a general system specification was derived and used to develop a concept for the container-integrated factory. A reconfigurable, modular manufacturing system is integral to the overall container concept. Production equipment was integrated in the form of interchangeable process modules, which can be quickly connected by standard utility supply and control interfaces. A modular and self-configuring control system provides assisted production workflow programming, while a modular process chain combining Additive Manufacturing, CNC milling, precision assembly and cleaning processes has been developed. A prototype of the container-integrated factory with reconfigurable process modules and control system has been established, with full functionality and feasibility of the system demonstrated.

Komputerowo wspomagane projektowanie dydaktycznego, modułowego, elastycznego systemu produkcyjnego

Komputerowo wspomagane projektowanie dydaktycznego, modułowego, elastycznego systemu produkcyjnego

Development of modular manufacturing systems—a review

Manufacturers throughout the world are facing major new challenges, including shorter product life cycles and increasing competition. As companies strive to rationalize engineering design, manufacturing, and support processes and to produce a large variety of products at lower costs, modularity is becoming a focus. This paper reviews the methodologies for determining modular manufacturing systems while considering cost and performance. The manufacturing concept, termed modular production systems and modular manufacturing systems are aimed specifically at “hard” low to medium technology products, as typified by goods such as children’s toys and kitchen appliances. It was proposed to increase the flexibility of the manufacturing operation in terms of its range of function, product, and service by modularizations and its ability to be easily reconfigured in the face of changing conditions.

Rate Monotonic Scheduling Analysis for Stability Constraints in Network Control System

The Feedback control system connected to a real time network through which the control process takes place are called network control system(NCSs).Features of NCS is the information like reference input, plant output, control input is exchanged between sensors, controllers, actuator using a network like CAN bus. The system wiring is reduced, easy to maintain and increases the system reliability. In the conventional control theories uses some ideal assumptions like equal distance sensing, synchronized control and non-delayed sensing and actuation. But in time varying systems this assumption fails due to transmission delay or packet dropout. In this paper Stability of NCS is analysed by considering transmission delay for a computer controlled system using scheduling algorithm The In direct digital control systems, computerized control replaced all analog instrumentation for the process control. Example system is shown in the figure 1 with a summary of several modular manufacturing system integrated control networks like FireWire, DeviceNet and Ethernet. In the example system, FireWire are used for the job requires high data throughput and high bandwidth. DeviceNet are used for the jobs which require low bandwidth like short, periodic messages signals transmission. Ethernet is preferred for the job like information exchange between the upper supervisory workstation and the controller is high volume but not time critical. Sensors with analog outputs and actuators with analog inputs are point to point connection with the digital computers. Sensing, actuating and control signal are deadline based since speed of all digital control CNC machines are high due to accuracy of the product manufacture in the system. Some of the constraints in the design of the system which affects the performance is choosing good scheduling algorithm, either constant or time varying network induced delay between the sensor to controller and controller to actuator in the shared medium, unreliable transmission path, packet dropouts due to packet size, bandwidth and busy path. Depending on the systems environmental condition while analysing some parameter are kept constant. Fundamental issues like time varying transmission period, network scheduling, network induced delay, single packet or multiple packet transmission of plant inputs and output and dropping of the network packets are basic problems in NCSs. In this paper we have considered time delay factor as variable since message transmitted between devices are either control data, which is time critical or information data which only needs guaranteed delivery.

Flexible, Self-configuring Control System for a Modular Production System

This paper presents a control concept of a modular manufacturing system (MPS). Having exchangeable process modules, the system can produce a wide range of products. For process modules a new concept for a Configuration and Information Memory (CIMory) is proposed. The CIMory provides a description of the module and its capabilities. Based on this information the control system, as well as the guidance system configures itself. The control follows a holistic approach with a hybrid structure to support both, modules with internal intelligence or with a simple command executing I/O unit. A Workflow Manager (WFM) organizes the production processes and the data exchange between all modules and the human-machine interface (HMI).