Shop Floor Operations Research Articles

A plug and produce framework for industrial collaborative robots

Collaborative robots are today ever more interesting in response to the increasing need for agile manufacturing equipment. Contrary to traditional industrial robots, collaborative robots are intended for working in dynamic environments alongside the production staff. To cope with the dynamic environment and workflow, new configuration and control methods are needed compared to those of traditional industrial robots. The new methods should enable shop floor operators to reconfigure the robot. This article presents a plug and produce framework for industrial collaborative robots. The article focuses on the control framework enabling quick and easy exchange of hardware modules as an approach to achieving plug and produce. To solve this, an agent-based system is proposed building on top of the robot operating system. The framework enables robot operating system packages to be adapted into agents and thus supports the software sharing of the robot operating system community. A clear separation of the hardware agents and the higher level task control is achieved through standardization of the functional interface, a standardization maintaining the possibility of specialized function features. A feasibility study demonstrates the validity of the framework through a series of reconfigurations performed on a modular collaborative robot.

Adaptive instructions to novice shop-floor operators using Augmented Reality

This paper presents a novel system using Augmented Reality and Expert Systems to enhance the quality and efficiency of shop-floor operators. The novel system proposed provides an adaptive tool that facilitates and enhances support on the shop-floor, due to its ability to dynamically customize the instructions displayed, dependent upon the competence of the user. A comparative study has been made between an existing method of quality control instructions at a machining line in an automotive engine plant and this novel system. It has been shown that the new approach outcompetes the existing system, not only in terms of perceived usability but also with respect to two other important shop-floor variables: quality and productivity. Along with previous research, the outcomes of these test cases indicate the value of using Augmented Reality technology to enhance shop-floor operators’ ability to learn and master new tasks.

Using autonomous intelligence to build a smart shop floor

The vision of smart shop floor is based on the notion of Industry 4.0 that denotes technologies and concepts related to Cyber-Physical Production Systems (CPPS). In smart shop floors, CPPS monitors physical processes, creates a virtual copy of the physical world, and makes decentralized decisions. CPPS allows virtual world to store data, process data, communicate, and cooperate with each other in real time. This paper presents architecture of smart shop floor based on physical, logical, and communication layers that embed intelligent approaches within manufacturing processes. Every physical entity in the smart shop floor is regarded as an autonomous intelligent logical unit that performs operations guided by distributed control functions. Moreover, computing power and optimization approaches are embedded into each logical unit to make decisions to agilely respond to frequent occurrence of unexpected disturbances at the shop floor. A test platform has been set up to demonstrate how physical entities can be cooperative and autonomous logical units that can automatize the shop floor operations. The results verify the feasibility and efficiency of the proposed method.

A state of the art system for managing time data in manual assembly

Valid time data, a prerequisite for the efficient use of manufacturing resources, directly influence planning and control quality. However, access to time data that capture real shop-floor operations in general and manual operations in particular is often assumed by both academics and practitioners. This has led to a mismatch between reality and the data found in systems for production planning and control, causing operational inefficiencies and negatively affecting decision-making in manufacturing companies. This article addresses the importance of updated and valid time data in planning and controlling production and considers how they relate to manufacturing system performance and improvement. The focus is on how to determine, utilise, and sustain valid time data for manual assembly operations through integrating enterprise information systems. The article builds on a case study performed at a large manufacturing enterprise that operates a state of the art system for managing time data in manual assembly. Findings from the case study reveal how standalone system applications can be integrated with the organisational functions of an enterprise to achieve updated and valid operation times.

Data and Information Handling in Assembly Information Systems – A Current State Analysis

Products become more complex as the general technology development reaches new levels. These new technologies enable manufacturing companies to offer better products with new functionalities to their customers. Complex products require adequate manufacturing systems to cope with changing product requirements. In general, manufacturing of this type of products entails complex structured and rigid IT systems. Due to the system's complexity and comprehensive structure, it becomes challenging to optimize the information flow. There are improvement potentials in how such systems could be better structured to meet the demands in complex manufacturing situations. This is particularly true for the vehicle manufacturing industry where growth in many cases have occurred through acquisitions, resulting in increased levels of legacy IT systems. Additionally, this industry is characterized by high levels of product variety which contribute to the complexity of the manufacturing processes. In manual assembly of these products, operations are dependent on high quality assembly work instructions to cope with the complex assembly situations. This paper presents a current state analysis of data and information handling in assembly information systems at multiple production sites at a case company manufacturing heavy vehicles. On basis of a certain set of characterizing manual assembly tasks for truck, engine and transmission assembly, this work focuses on identifying what data and information that is made available to operators in terms of assembly work instructions and the importance of such data and information. This work aims to identify gaps in the information flow between manufacturing engineering and shop floor operations.

Assisted Hardware Selection for Industrial Collaborative Robots

This paper presents a configuration framework for assisting shop floor operators in selecting a suitable hardware configuration from commercially available components. The primary focus of this work is the modeling of process, product, and equipment knowledge, and the design of a configurator tool implementing this knowledge. The configurator takes process and product information as input and derives a list of suitable components for the operator to choose from. The approach is verified through a preliminary study indicating the feasibility of the approach.

Testing order review and release mechanisms to improve flow time: a multi-method approach

For decades, various improvements in shop floor performance due to work load control (WLC) and order review and release (ORR) systems have been reported. The majority of these studies rely only on computer simulation to demonstrate their benefits, which typically include minimising resource idleness or order tardiness, among others. However, the vast majority of these studies do not test these mechanisms in real-world shops, thus limiting the research in this area. Using the 'theory-practice iterative cycle', this study employs a combination of case study, computer simulation, and action-research to develop and empirically test a new ORR mechanism that improves mean system flow time (MST) through shortest setups (SSU). This is important because extant simulation studies do not support the proposition that ORR improves MST. The SSU mechanism led to improvements in MST of 25% in simulation studies and 7% in a real-world firm, among other benefits. Additionally, we discuss a number of issues related to field research in ORR that may benefit researchers working on completing the theory-practice cycle.

The Comparison Study of Different Operator Support Tools for Assembly Task in the Era of Global Production

As part of a global production strategy, many manufacturing companies locate their assembly plants in different countries around the world. While outsourcing final assembly closer to key markets has competitive benefits, these companies face new challenges with communication and dissemination of information. Concerning shop-floor operators specifically, these challenges affect the initial training and continuing improvement work instructions in particular. Emerging information and communication technology (ICT) have created new opportunities for supporting operators cognitively. In this paper, an immersive virtual reality (IVR) training environment for LEGO gearbox assembly was developed and tested. IVR technologies offer new opportunities where operators can access training and work instructions in an immersive environment, which could potentially improve and influence the operator performance and emotion. Both objective performance and subjective emotion were measured and the impacts were analyzed. The results were compared with four different operator support approaches and it was seen that IVR technology has the potential of improving operator and that further studies on integration, information, communication design and development of measurement methods are needed before the industry can benefit from the full potential of IVR technology.

Augmented Reality Smart Glasses in the Smart Factory: Product Evaluation Guidelines and Review of Available Products

Augmented reality smart glasses (ARSG) are increasingly popular and have been identified as a vital technology supporting shop-floor operators in the smart factories of the future. By improving our knowledge of how to efficiently evaluate and select the ARSG for the shop-floor context, this paper aims to facilitate and accelerate the adoption of the ARSG by the manufacturing industry. The market for ARSG has exploded in recent years, and the large variety of products to select from makes it not only difficult but also time consuming to identify the best alternative. To address this problem, this paper presents an efficient step-by-step process for evaluating the ARSG, including concrete guidelines as to what parameters to consider and their recommended minimum values. Using the suggested evaluation process, manufacturing companies can quickly make optimal decisions about what products to implement on their shop floors. This paper demonstrates the evaluation process in practice, presenting a comprehensive review of currently available products along with a recommended best buy. This paper also identifies and discusses topics meriting research attention to ensure that the ARSG are successfully implemented on the industrial shop floor.

Processes improvement applying Lean Office tools in a logistic department of a car multimedia components company

Companies that implemented Lean Production in shop-floor operations continuously search for new improvements opportunities. Indirect or support areas such as logistic departments has a lot of such opportunities. This was the case of the company of the study presented in this paper. Thus, this paper presents some results of a project that explored the improvement opportunities of a raw materials management of a Logistics department by application of Lean Office tools. This department is responsible for the management of raw materials, track and report of key functional metrics to improve logistic effectiveness. In spite of well organized, when looked through a Lean lens some opportunities emerged as many wastes were identified, namely, lack of information integration and visibility and, consequently, low data processing efficiency. To eliminate such wastes, some tools were applied such as 5S, Poka-Yoke mechanisms, Standard Work and Visual Management. The results were very satisfactory being some of them: greater transparency of the processes, better definition of priorities in the tasks to be performed and better organization and work time management.

Selective maintenance optimization under schedule and quality constraints

Purpose – The traditional practice for maintenance, quality control and production scheduling is to plan independently irrespective of an interrelationship exist between them. The purpose of this paper is to develop an approach for integrating maintenance, quality control and production scheduling. The objective is to investigate the benefits of the integrated effect in terms of the expected total cost of system operation of the three functions. Design/methodology/approach – The proposed approach is based on the conditional reliability of the components. Cost model for integrating selective maintenance, quality control using sampling-based procedure and production scheduling is developed using the conditional reliability. An integrated approach is such that, first an optimal schedule for the batches to be processed is obtained independently while the maintenance and quality control decisions are optimized considering the optimal schedule on the machine. The expected total cost of conventional approach, i.e. “No integration” is calculated to compare the effectiveness of integrated approach. Findings – The integrated approach have shown a higher cost saving as compared to the independent planning approach. The approach is practical to implement as the results are obtained in a reasonable computational time. Practical implications – The approach presented in this paper is generic and can be applied at planned as well as unplanned opportunities. The proposed integrated approach is dynamic in nature, as during maintenance opportunities, it is possible to optimize the decision on maintenance, quality control and production scheduling considering the current age of components and production requirement. Originality/value – The originality of the paper is in the approach for integration of the three elements of shop floor operations that are usually treated separately and rarely touched upon by researchers in the literature.

Benchmark the best factory data collection system (FDC) using AHP-GRA method

Purpose – The purpose of this paper is to propose a multi-criteria decision making method to evaluate factory data collection (FDC) system alternatives. Design/methodology/approach – “Information” in is fundamental resource to the success of any business which is as valuable as capital or people. The factory data (information) collection system (FDC system) consists of the various paper documents, terminals, and automated devices located throughout the plant for collecting data on shop floor operations for compiling and processing the data. In this paper, nine alternatives of FDC methods are evaluated on the basis of eight criteria. The weight of each criterion is determined using Analytic Hierarchy Process, and the same weights are used to evaluate alternatives of FDC system using Grey Relational Analysis – A multi-criterion decision making method. Findings – The methodology facilitates the selection of the best FDC system that will minimize the data entry time and chances of errors. The methodology suggests Radio-Frequency Identification (RFID) system is the most preferred choice (ideal) among the nine alternatives whereas Operation tear strips is the worst solution. Originality/value – The proposed methodology will provide a useful tool to the decision maker, which may help to eliminate the associated risks during data entry. The selected best FDC system, i.e. RFID is most suitable tool for ERP system to integrate internal (manufacturing) and external (sales and service) management information system.

Why I want to be a Future Swedish Shop-floor Operator

When looking in rear view mirrors the Swedish as well as the international production industries can overview several years of progress covering all aspects of production. Production methodologies and machines etc. have changed and evolved, and so has the environment of the shop-floor operator. The demands on the shop-floor operators have grown from simple monotonic tasks with low complexity to pro-active team work requiring flexibility, continuous improvements and a holistic approach.With a base in a study where production and HR-managers at six Swedish manufacturing industries have been interviewed this paper identifies the role of today's and the future Swedish shop-floor operator. The response to the described role of the future operator is compiled from the ones who will become the future Swedish shop-floor operators – today's teenagers attending technical high-school. Their views of the environment of the future shop-floor operator are described by accuracy, development, a good working environment and team work. The paper also reveals what the offer should include to make these teenagers say: I want to be a future Swedish shop-floor operator.

Using Autonomous Intelligence to Build a Smart Shop Floor

The vision of smart factory is based on the notion of Industry 4.0 that denotes technologies and concepts related to cyber-physical systems and the Internet of Things (IoT). In smart factories cyber-physical systems monitor physical processes, create a virtual copy of the physical world and make decentralized decisions. Over the IoT, cyber-physical systems communicate and cooperate with each other in real time. This paper presents a smart factory architecture based on communication and computing layers that embed scheduling mechanisms within a mechanical shop floor. Every physical entity in the shop floor is seen as an autonomous intelligent agent that performs tasks guided by dynamic scheduling functions. A test bed has been set up to show how physical entities can be cooperative and autonomous units that can automatize the shop floor operation processes. The results verify the feasibility and efficiency of proposed method.

Cross-docking Operation Scheduling: Truck Arrivals, Shop-Floor Activities and Truck Departures

Cross-docking is a relatively new logistic strategy which seeks to make economies in transportation, decrease lead time and reduce inventory. The main principle is to unload, sort, consolidate and transfer delivered packages from inbound trucks to outbound trucks, with a minimum of storage or treatment in between. Two key issues associated to this field are the truck scheduling and the shop-floor operation scheduling. We propose a mixed integer linear programming model to schedule truck arrivals, shop-floor activities and truck departures. The cross-dock configuration we study is based on an industrial case on the automotive industry. In particular, a repack operation and two temporary storage zones are considered. The objective is to minimize internal operation cost (penalty related to extra capacity needs) and outbound transportation cost (number of trucks). The model is implemented and tested in CPLEX with small size instances, based on industrial data. The proposed model could be easily adapted to a variety of cross-dock configurations, in terms of internal capacity and cost distribution.

Determining the Effect of Process Control Parameters on Tool - Chip Interface Temperature during Hard Turning of AISI D3 Tool Steel in Dry Condition

Hard turning is recent upcoming technology through which surface quality of machined components can be enhanced while comparing with the traditional grinding method. Since the absence of metal cutting fluids during this process, numerous harmful effects on shop floor operators and possible negative impacts on environment can be eliminated. Normally some of the vital machinability aspects such as surface integrity of machined parts has been influenced by magnitude of cutting temperature which evolved in metal cutting interface. Therefore in this experimental investigation, the influence of various process control parameters on tool-chip interface temperature was evaluated during hard turning of AISI D3 tool steel in dry condition. The machining trials were conducted as per the L9 Taguchi DOE approach and subsequent experimental data were analysed with the use of Design-Expert® V7 statistical software. This experiment results revealed that feed rate is having predominant influence in determining the magnitude of cutting temperature followed by depth of cut and cutting speed whereas the influence of cutting tool nose radius is insignificant.

Reliable shop floor bottleneck detection for flow lines through process and inventory observations: the bottleneck walk

Bottleneck detection in manufacturing is the key to improving production efficiency and stability in order to improve capacity. Yet, common bottleneck detection methods in industry and academia lack either accuracy or practicability, or both, for dynamic systems. The new methodology is conducted by the observation of processes and inventories. Blocked processes and full inventories indicate a downstream bottleneck. Starved processes and empty inventories indicate an upstream bottleneck. Through subsequent observations of multiple process states and inventory levels within a system, it is possible to determine the direction of the bottleneck at the given time and hence to find the momentary bottleneck in the system. The shifting of bottlenecks can be observed directly. Work sampling techniques can be used to obtain a long-term picture of the dynamically shifting bottleneck. The new methodology does not require any calculations, statistics, or time measurements. Hence, the method is suited for practical use by shop floor supervisors and clerks. The direct observation of the bottleneck also gives additional information about the underlying causes of the bottlenecks, simplifying the improvement of the system capacity. Extensive field testing of the method received positive feedback not only from management but also from shop floor operators. The method is already in use at the Robert Bosch GmbH, where it is known as the bottleneck walk.

Design of a High Accuracy 3-Axis Coordinate Measuring Machine Working on the Shop Floor

One of the key features of advanced manufacturing technologies is the metrology of geometric quantities. Coordinate measuring machines (CMMs) now are widely used to perform relevant measurements. Normally, the use of CMMs in traditional quality control rooms, isolated from the production floor, often proves unsuitable for effective and timely feedback on the manufacturing process. However, CMMs are sensitive to environmental factors such as humidity, suspended dust and oil, vibrations, and especially temperature. For this reason, measuring machines must to be designed with features that make them more resistant to the environmental influences on shop floor operations. The main goal of this work is to enhance accuracy of a CMM working on the shop floor conditions by design improvements and error compensation. A 3-axis CMM will be built with some improved designed features and a software compensation technique will be applied to enhance the machine accuracy.

Experience in using computer technologies for university training of future NPP personnel based on “University-Enterprise” program

This paper considers aspects of a program for training future nuclear power plant personnel developed by the NPP Department of Ivanovo State Power Engineering University jointly with the Kalinin NPP. The program components include application of computer modeling and simulation in the university-based studies and the “8th term” project for studies in the nuclear plant environment. During the 8th term, students acquire practical skills in carrying out shop-floor operations and undergo training at the plant's training center where examinations are also taken. The university-based studies include computer modeling for numerical experiments in kinetics of water-cooled water-moderated nuclear reactors in the Mathcad environment. Processes are simulated using the VVER-1000 unit computer and full-scale simulators.Software packages and procedural guides have been developed for mathematical modeling of reactor transients; simulation programs and procedures for the computer and full-scale simulators of neutron experiments and plant startup/shutdown operations have also been developed. Integrated training systems contribute to promoting occupational mentality and form an efficient tool for the personal development of future staff, so most attention in the use of simulators is given to the effects of individual qualities on the level of success achieved at the given stage of training. For illustration, a mathematical model is described and results from numerical experiments to study the reactor xenon stability are presented. Integrated implementation of the described training programs makes it possible to cut practically by half the period for the university graduates to adapt themselves to plant environment as confirmed by reports from the leaders of respective departments.

Aligning decision support with shop floor operations: a proposal of intelligent product based on BDI physical agents

Multi-agent system (MAS) models have the drawback of an excessive dependence on up-to-date field information and on complex interaction protocols. This work proposes a theoretical and experimental agent-based decision support system (DSS) architecture that is designed and developed to align shop floor operations, but including the radio frequency identification (RFID) information feedback. This product-driven MAS has been structured on a split organization model to enforce the idea of division between physical elements and information and communication technology. The proposed MAS framework, called MAS-DUO, has been tested at the ground-handling operations at the Ciudad Real Central Airport and in a simulated logistics centre at the Autolog Labs-UCLM. This paper introduces the beliefs–desires–intentions (BDI) physical agents of this framework as the core of this new approach, a new vision that mixes BDI reasoning, RFID and the Markov decision process.