Small Lot Sizes Research Articles

Mitigating risks of digitalization through managed industrial security services

Digitalization has become a cornerstone of competitiveness in the industrial arena, especially in the cases of small lot sizes with many variants in the goods produced. Managers of industrial facilities have to handle the complexity that comes along with Industry 4.0 in diverse dimensions to leverage the potentials of digitalization for their sites. This article describes major drivers of this complexity in current industrial automation to outline the environment of today's challenges for managers of this technical transition--and shows how managed industrial security services can contribute to stabilize the industrial system. An outlook is given to future automation scenarios as well as the major concepts involved in their protection.

Integrated Product, Production and Material Definition for Conventional versus Generative Manufacturing Technologies

Generative or additive manufacturing is today getting more and more an appropriate de-facto standard in industrial production. The often-cited “industrial revolution from the printer” exhibits enormous potentials even concerning a creative design freedom as well as huge varieties in flexibility (e.g., a broadening diversification of the individual product spectrum associated with small lot sizes). In contrast, however, conventional manufacturing technologies within the automotive industry, for instance, still point out benefits with regard to process stability, automation, productivity, but also quality assurance.Set against this background, and to support the systematic and increasingly industrialized application of additive manufacturing (AM) in industry, this contribution presents a scientifically detailed view on a methodological set-based approach, which provides a technical, economic and ecological significance in terms of choosing the right manufacturing technology, associated with its principle design and appropriate material already in the early phase of product development.

Distributed Motion Planning for Industrial Random Bin Picking

The task of bin picking is to automatically unload objects from a container using a robotic manipulator. A widely used solution is to organize the objects into a predictable pattern, e.g., a workpiece carrier, in order to simplify all integral subtasks like object recognition, motion planning and grasping. In such a case, motion planning can even be solved offline as it is ensured that the objects are always at the same positions. However, there is a growing demand for non-structured bin picking, where the objects can be placed randomly in the bins. This arises from recent trends of transforming classical factories into smart production facilities allowing small lot sizes at the efficiency of mass production. Due to unknown positions of the objects in the non-structured bin picking scenario, trajectories for the manipulator cannot be precomputed, but they have to be computed online. Sampling-based motion planning methods like Rapidly Exploring Random Tree (RRT) can be used to plan the trajectories. In this paper, we propose a modification of RRT for distributed motion planning aiming to reduce the runtime. The planning task is first simplified by computing several guiding waypoints. The waypoints are distributed to a set of planners running in parallel and each planner computes a short trajectory between two given waypoints. Connecting the waypoints is easier than solving the original task, therefore each planner runs fast. In comparison to other parallel motion planning techniques, the proposed approach does not require any communication among the computational nodes, which is more suitable for cloud-based computing. The proposed work has been verified both in simulation and on a prototype of a bin picking system.

An IoT-based Platform for Automated Customized Shopping in Distributed Environments

Today’s manufacturing enterprises often face the challenge of manufacturing highly customized products in small lot sizes. One solution to adapt to the ever-changing demands that increases resources flexibility, lies in the digitization of the manufacturing systems. This work proposes an open and interoperable Internet of Things platform, enhanced by innovative tools and methods that transform them into Cyber-Physical Systems, supporting smart customized shopping, through gathering customers’ requirements, adaptive production, and logistics of vending machines replenishment. This platform, exploiting cloud technology capabilities, enables contactless/ cashless payment solutions, smart sensing and control, advanced reporting, as well as ubiquitous data access and visualization.

Sustainability impact of digitization in logistics

Today, most enterprises are undergoing a digitization process with the fourth industrial revolution, named industry 4.0. The focus of the digital transformation lies mainly on production, therefore the terms such as “Factory of the Future” or “Smart Factory” are used similar with this concept. However, there are many reasons for considering the impact of digitalization in logistics and the importance of supply chain for industry 4.0. The key promises of this concept are enabling real-time full-transparency from suppliers to customers, small lot sizes, multiple product variants, connected processes and decentralized, autonomous management. These benefits cannot be achieved by production alone, but only along the entire supply chain. Moreover, logistics should gain a greater vision to fulfill the requirements of industry 4.0 as sustainably as possible in terms of using appropriate technologies and enhancing vertical and horizontal integration among the supply chain partners. In this respect, this study highlights the benefits of the digitization of logistics process and examines the sustainability impact of digitization in logistics. The study is pursued as a single case study within the FMCG companies and their transport service providers in Turkey and it is based on a qualitative method and on connected semi-structured interviews.

Designing number of Kanban in glove box assembly

For many decades, Just-In-Time manufacturing and lean manufacturing have adopted kanban system as a mean to control inventory and production. A number of tagged kanban cards represents inventory of the system, whereas untagged kanban cards equate to production orders. The ideal conditions are a consistent product mixed with a small production lot size and minimum setup time. Such conditions are difficult to obtain even in many automotive assembly lines similar to a case study. The case study assembly line is a glove box assembly production line that assembles two plastic parts and wields them together with a vibration machine after positioning in a mold designed for different products. Because of storage equipment, each kanban card represents 60 identical glove boxes. Therefore, a production engineer re-schedules the production planning to minimize the numbers of changeover without any effect on downstream. This ad hoc production scheduling leads to urgent production orders and interruption of lot size. As a result, the factory embeds historical data into a computer simulation that accounts for current molds, receiving time, and numbers of pending kanban cards, as well as number of storage equipment. The results of this simulation reveals that scheduling criteria and suggest a suitable lot size if the factory decides to change a storage equipment.

Geometry-dependent parameterization of local support in robot-based incremental sheet forming

This article describes new developments in an incremental, robot-based sheet metal forming process for the production of sheet metal components for small lot sizes and prototypes. The dieless kinematic-based generation of the sheet metal’s shape is implemented by means of two industrial robots, which are interconnected to a cooperating robot system. With the help of this system, an experimental survey has been carried out to examine the influence of the support force and the support angle of the supporting tool on the geometric accuracy. Their influence is illustrated with the help of various experimental results shown and interpreted within this article.

Intuitive robot programming through environment perception, augmented reality simulation and automated program verification

The increasing complexity of products and machines as well as short production cycles with small lot sizes present great challenges to production industry. Both, the programming of industrial robots in online mode using hand-held control devices or in offline mode using text-based programming requires specific knowledge of robotics and manufacturer-dependent robot control systems. In particular for small and medium-sized enterprises the machine control software needs to be easy, intuitive and usable without time-consuming learning steps, even for employees with no in-depth knowledge of information technology. To simplify the programming of application programs for industrial robots, we extended a cloud-based, task-oriented robot control system with environment perception and plausibility check functions. For the environment perception a depth camera and pointcloud processing hardware were installed. We detect objects located in the robot’s workspace by pointcloud processing with ROS and the PCL and add them to the augmented reality user interface of the robot control. The combination of process knowledge from task-oriented application programming and information about available workpieces from automated image processing enables a plausibility check and verification of the robot program before execution. After a robot program has been approved by the plausibility check, it is tested in an augmented reality simulation for collisions with the detected objects before deployment to the physical robot hardware. Experiments were carried out to evaluate the effectiveness of the developed extensions and confirmed their functionality.

HPC-milling of WC-Co cemented carbides with PCD

In order to machine wear parts of small lot size made out of WC-Co cemented carbides, milling can be an economically promising alternative to grinding or electrical discharge machining (EDM) for finishing after sintering. However, milling of sintered cemented carbides implies a high risk of tool failure up to now.Based on initial feasibility studies on milling of medium Co-content carbides with PCD, the potential and limitations of this technology need to be evaluated especially with regard to suitable cutting edge geometries and cutting parameters.Major aspects of the investigations performed for varying cutting edge chamfers, radial depths of cut and cutting velocities were chip formation, cutting forces, tool wear, surface roughness and the integrity of the boundary zone. Results indicate, that machining with a tool diameter of D=10mm at axial depths of cut within the range of sintering allowances (≈0.2mm) is possible at material removal rates which can be called high productivity conditions (HPC) compared to the state of the art. Experiments show specific wear formation, hardness increase of the machined surface and change of the microstructure in the boundary zone.

Strategies to Empower Existing Automated Material Handling Systems to Rising Requirements

Due to reasons like higher flexibility demands, smaller lot sizes in production, and tool upgrades leading to higher throughputs, existing automated material handling systems are facing ever rising requirements. At the same time, the potential to upgrade transport system hardware is limited due to technical reasons as well as its interconnected nature. This paper, therefore, focuses on new possibilities regarding the integration of already existing but not yet used information into automated material handling system (AMHS) control, and presents three different approaches for improvement: 1) improving empty vehicle management strategies by incorporating near-future transports demands; 2) balancing track utilization by adjusting path selection processes; and 3) interaction between AMHS and scheduling/dispatching, in order to consider potential bottle-necks. Each of these approaches improves AMHS performance; in combination they have the potential to empower the system to handle future demands with little or no hardware manipulations.

Scheduling and Control of Startup Process for Single-Arm Cluster Tools With Residency Time Constraints

Due to the trends of larger wafer diameters and smaller lot sizes, cluster tools need to switch from processing one lot of wafers to another frequently. This leads to more transient periods in wafer fabrication, which includes startup and close-down processes. Their efficient scheduling and control problems become more and more important. They become very difficult to solve especially when wafer residency time constraints must be considered. Most previous studies focused on the steady periodic schedule for cluster tools. Little research was on the transient processes of cluster tools despite their increasing importance. In order to optimize a startup transient process, this work develops a Petri net model to describe its behavior for a single-arm cluster tool. Then, based on the model, for the case that the workloads among the steps can be properly balanced, this work proposes a scheduling algorithm to find an optimal and feasible schedule for the startup process. For the other cases schedulable at the steady state, a linear programming model is developed to find an optimal and feasible schedule for the startup process. Finally, illustrative examples are given to show the applications of the proposed method.

Special Issue on Green and Lean Production

Green production for a sustainable world has increased in importance as society has increased in its awareness of global warming, energy security, pollution, and the metals shortage. Lean production is a concept considered in successful manufacturing enterprises. Green and lean are often achieved together, such when both waste and energy consumption are reduced. On the other hand, the two are sometimes thought to be at odds, such as when the frequent transportation and small lot size often used in lean production consumes more energy usage than does conventional production. The integration of green and lean is familiar to those who study sustainability. The three bottom lines of sustainability are ecological, economic, and social sustainability. The ecological and economic dimensions have been discussed in the field of production systems. Proactive scenario simulation is required for the evaluation of sustainability as well as for the discussion of integrated criteria of sustainability. This special issue covers both green and lean topics in the production field. It considers the challenges that need to be addressed so that researchers and practitioners may engage in scientific and practical discussions of these topics. Six contributions from academic institutes and six contributions from manufacturing companies have been accepted. This special issue is expected to encourage both academics and practitioners to discuss future collaboration. Most contributions deal with integrated green and lean issues. Some academic papers evaluate sustainability. Case studies as technical papers or development reports have been provided by industrial contributors. Methodologies range from survey to life cycle assessment to simulation to implementation. The applications range from machine development for green production to national technical policy for sustainable manufacturing. All papers were refereed through careful peer reviews. We would like to express my sincere appreciation to the authors for their submissions and to the reviewers for their invaluable efforts, as together they made possible the publication of this special issue.

Information processing structures and decision making delays in MRP and JIT

Prior literature has asserted that higher supply chain visibility, concerned with better information flow and determining more accurate demand levels within the supply chain at a given time, improves decision-making efficiency. Decision-making efficiency denoted by decision-making delay is in turn dependent on the information processing structure. Different production control systems have different information processing structures. This paper considers the relations between the production control system (MRP and JIT) and the organization structure of information processing that determines the decision making delay. We compare MRP and JIT across different information processing structures and decision efficiency, and find that JIT is suitable for small lot size and large variety production and MRP for large lot size and small variety production. In addition, an optimized organization structure of information processing will surely reduce the decision making delay.

“Industrie 4.0” and Smart Manufacturing – A Review of Research Issues and Application Examples

A fourth industrial revolution is occurring in global manufacturing. It is based on the introduction ofInternet of thingsandservitizationconcepts into manufacturing companies, leading to vertically and horizontally integrated production systems. The resultingsmart factoriesare able to fulfill dynamic customer demands with high variability in small lot sizes while integrating human ingenuity and automation. To support the manufacturing industry in this conversion process and enhance global competitiveness, policy makers in several countries have established research and technology transfer schemes. Most prominently, Germany has enacted itsIndustrie 4.0program, which is increasingly affecting European policy, while the United States focuses onsmart manufacturing. Other industrial nations have established their own programs on smart manufacturing, notably Japan and Korea. This shows that manufacturing intelligence has become a crucial topic for researchers and industries worldwide. The main object of these activities are the so-called cyber-physical systems (CPS): physical entities (e.g., machines, vehicles, and work pieces), which are equipped with technologies such as RFIDs, sensors, microprocessors, telematics or complete embedded systems. They are characterized by being able to collect data of themselves and their environment, process and evaluate these data, connect and communicate with other systems, and initiate actions. In addition, CPS enabled new services that can replace traditional business models based solely on product sales. The objective of this paper is to provide an overview of the Industrie 4.0 and smart manufacturing programs, analyze the application potential of CPS starting from product design through production and logistics up to maintenance and exploitation (e.g., recycling), and identify current and future research issues. Besides the technological perspective, the paper also takes into account the economic side considering the new business strategies and models available.

Teaching Smart Production: An Insight into the Learning Factory for Cyber-Physical Production Systems (LVP)

Increasing global competition among producing companies necessitates a further specialization and continuous enhancement of products, manufacturing processes and business models. The current advances in these areas are highly influenced by the digitization, which might not only change the work environment within a factory but might also change entire value-added chains. Therefore, producing companies express their demand for learning environments, which address ongoing developments regarding digitization and Industry 4.0.This paper presents the concept for the learning factory for cyber-physical production systems (LVP). Based on a production scenario, which includes manufacturing as well as assembly, the learning environment demonstrates how recent technologies can be used to cope with high numbers of product variants and small lot sizes. The technologies utilized within the LVP include interactive assistance systems for workers, real-time business intelligence and simulation tools for single processes and for the overall material flow. The learning factory shows the technical implementation of these technologies as well as their impact on the organization of the production system. By attending one of the interactive training sessions, participants can experience the various advantages of intelligent production systems.

Simulation of Production Processes Involving Cyber-physical Systems

It has become common practice to apply simulation during product development and production planning. The increasing demand for individualized goods requires the ability to produce in small lot sizes and therefore more flexible resources, which leads to the use of cyber-physical systems (CPS) in manufacturing. This papers aims to look at the changing requirements, pitfalls and possible solutions when applying simulation to CPS. The research is based on a case study of a large car manufacturing company that has already implemented CPS in one production line. The paper will also provide an overview of simulation types and discuss their fitness.

Joule heating of the forming zone in incremental sheet metal forming: Part 1

Incremental sheet metal forming for the production of parts in small lot sizes is of growing interest both in research and in industry. Recently, incremental sheet metal forming at elevated temperatures has been investigated concerning reduced forming forces, reduced springback, increased geometrical accuracy of the formed parts and its applicability for hard-to-form materials. This paper gives an overview of the used heating methods in a state-of-the-art analysis. It focuses on regional Joule heating of the moving forming zone with up to two moving forming tools. The theoretical background is presented for Joule heating and occurring electrical resistances in the setup. After delivering a process design to achieve the desired characteristics, this work presents a simplified model for the calculation of the temperature of the forming zone.

Integration of the vertical warp stop motion positioning in the model-based self-optimization of the weaving process

The warp tension is a critical variable of the weaving process. If the warp tension is too high or too low, the weaving process will be interrupted. In order to find a suitable setting for the weaving machine, the experience of the operator is needed. Self-optimization routines can support the operator in finding optimal settings. Within this paper, the model-based self-optimization of the weaving process developed at Institut fur Textiltechnik der RWTH Aachen University is presented. The self-optimization routine uses an automatic design of experiment to generate data for a full quadratic regression model of the characteristic values of the warp tension. Three weighted quality criteria are used to optimize the machine settings within given boundaries. An improvement is proposed by integrating the vertical warp stop motion position as a factor with high impact on the warp tension. The vertical warp stop motion position is automated and integrated into the optimization process. The adjusted routine is validated on an air jet weaving machine. The test results show that the integration of the warp stop motion position into a self-optimization routine leads to a 35% reduction of tension in the warp yarns. Compared to the existing routine, the integration of the warp stop motion position leads to a 23% higher effect on the warp tension as the target value of the optimization. The statistical validation shows that the quality of the used regression model is high. The described system also reduces the setup time of a weaving machine. Economically, the improvements mean a reduction of production costs by 22%, when producing small lot sizes. The system therefore contributes to the competitiveness of weaving mills in high-wage countries.

How does parking interplay with the built environment and affect automobile commuting in high-density cities? A case study in China

This study investigates an important but often overlooked problem – the interaction between parking and land use – to examine the effects of the built environment on car commuting. Using the case of Shenzhen, China, a structural equation model is employed to examine the tripartite relationship among the built environment, parking supply and car commuting. The parking–built environment relationship partly reflects the parking supply mechanism that is collectively influenced by the parking market and regulations. The results indicate that, because of the high cost of constructing parking, property developers are reluctant to build sufficient parking spaces for the residential population in densely built neighbourhoods with small lot sizes. However, minimum parking standards often lead to more parking provisions in dense central locations. Therefore, the benefits of compact land use and transit-oriented development (TOD) for reducing car use are either reinforced or offset depending on the various interrelationships between parking and the built environment. In the context of policy implications, a fine-grained urban fabric should be particularly supported, considering its significant effects in reducing car commuting, as well as its potential role in fostering a well-functioning parking market. Meanwhile, imposing parking caps in dense and central areas would be wise because parking oversupply encourages more car trips, which counteracts the sustainable merits of dense developments.

Single Machine Scheduling Based on EDD-SDST-ACO Heuristic Algorithm

Abstract A large number of changeovers exist in multi-item and small lot size production mode, which lead to a long setup time and significantly influence productivity. However, setup time has received significantly less attention in previous studies regarding the single machine scheduling (SMS) problem. This paper investigates the SMS problem with sequence-dependent setup time (SDST). First, a model of SMS-SDST is developed to minimise the makespan. An earliest due date (EDD), SDST, and ant colony optimisation (ACO) heuristic algorithm is presented. In order to evaluate the performance of the proposed algorithm, Taguchi’s robust design method is employed to define the best parameter values. Related results are analysed by statistical tools. The computational experiments are compared with an ACO algorithm and a genetic algorithm. The experimental results and statistical analyses show that the proposed EDD-SDST-ACO is effective for the problem.