Shop Floor Information Research Articles

Concept Design of a Digital Shop Floor Information System for Assembly Operators in Machine Industry

Industry 4.0 and digitization are currently changing shop floor management in production. Especially in the production of highly customized and individual products, digitization offers many opportunities for more efficient processes. Providing the right information in the right time at the right place can help to reduce lead time as well as production costs. This paper shows the use of Axiomatic Design to develop a conceptual design for an innovative and digital shop floor information system for supporting assembly operators in machine industry in their daily work. The research is based on a real industrial case study with a medium sized manufacturer of customized machines. Needs from practice were collected through workshops with the industry partner and were translated into functional requirements. These functional requirements were derived with an Axiomatic Design decomposition to design solutions. The results of the AD analysis were used as a basis for the concept design of an operator information system in the company.

Verification of ERP Standard Time Using TOC Technique and Improvement of MES Routing Point

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

Lean Information and Communication Tool to Connect Shop and Top Floor in Small and Medium-sized Enterprises

In small and medium-sized enterprises (SME), information acquisition and transmission between business departments is carried out mainly in a paper-based way. For instance, in manufacturing and assembly, the modifications of technical drawings are documented manually on technical drawings. At the end of the production process, all technical drawings have to be forwarded to the design/development department. Nowadays, all these drawings are passed over, in order to create an overall machine documentation. The technical drawing and machine modifications have to be reviewed successively which increases both the completion time and project term. Furthermore, it increases the risk of consequential errors. Moreover, it is personal intensive, which results in a delayed engineering documentation for the customer. To overcome this ineffective process, a computerized production application in combination with smart devices was developed. This shop floor information application supports employees with recording and communication of modifications of components and technical drawings. The tool for Industry 4.0 focuses on different business departments and business processes to digitalize the previously described analog processes and avoid media gap in the company.

An algorithm for data-driven shifting bottleneck detection

AbstractManufacturing companies continuously capture shop floor information using sensors technologies, Manufacturing Execution Systems (MES), Enterprise Resource Planning systems. The volumes of data collected by these technologies are growing and the pace of that growth is accelerating. Manufacturing data is constantly changing but immediately relevant. Collecting and analysing them on a real-time basis can lead to increased productivity. Particularly, prioritising improvement activities such as cycle time improvement, setup time reduction and maintenance activities on bottleneck machines is an important part of the operations management process on the shop floor to improve productivity. The first step in that process is the identification of bottlenecks. This paper introduces a purely data-driven shifting bottleneck detection algorithm to identify the bottlenecks from the real-time data of the machines as captured by MES. The developed algorithm detects the current bottleneck at any given time, the ave...

Characterization of continuous precise workload control and analysis of idleness penalty

The variability in the market conditions is growing in terms of its frequency of change and range of diversity. In response to this new industrial panorama, research on production systems is aiming to achieve highly reconfigurable shop floors. Frequent changes in such systems require also frequent re-planning with updated information. In this regard the Continuous Precise Workload Control method, is a recent approach aiming at precise control of workload in shop floor with the use of direct load graphs. Supported by a multi-agent platform, it generates dynamic non-periodic release decisions exploiting real time shop floor information. The study in this paper is two folded; (1) the presented workload approach is defined in terms of eight dimensions of the workload control concept in order to highlight its distinctive characteristics and (2) the impact of idleness penalty factor is analyzed by an experiment design in order to investigate its effect on the job release decision. The results show that the idleness penalty factor decreases the idleness of the resources up to a point where the adverse effect is initiated.

Common-HMI for the monitoring of heterogeneous equipment

Rapid changes in the global economic environment and advancement of converging technology have been accelerating the digitalization of the manufacturing industry. In particular, digitalization is being magnified as one of the major contributors for manufacturers to secure competitive edge — such as better productivity and reduction of transaction cost — as well as the main culprit of gaps in growth. It is drastically changing the paradigm of business management. The manufacturing industry has been striving to cope with these changes by adopting some types of production management systems but having difficulties about how to collect 4M (Machine, man, materials and manufacturing resources) data effectively and how to integrate dispersed information systems following the expansion of production lines as well as the cost of adopting a new system. As the essential components of automation, HMI (Human machine interface) is designed to monitor the operation of equipment and collects the shop floor information. HMI relies heavily on equipment and should be different for different manufacturers as well as within same manufacture; thus inevitably imposing a heavy burden on HMI developers. This paper introduces a common-HMI that is capable of collecting data for heterogeneous equipment in the shop floor and presenting clear, visual information to the user. The common-HMI is reusable for different types of production equipment and can be deployed without any modifications; it is expected to save on system adoption cost and the proposed method can facilitates system expansion and maintenance effort allowing the expansion of the production line. It has proven its outstanding performance including reusability and reduction of system adoption cost in a pilot study wherein it was used for two different types of equipment.

Continuous Integration of Field Level Production Data into Top-level Information Systems Using the OPC Interface Standard

On the way to the fourth industrial revolution, one major requirement lies in reaching interoperability between hardware and software systems. Especially real-time propagation of shop floor information in top-level production planning and control systems as well as the consolidation of distributed information into a consistent data basis for comprehensive data analysis are still missing in most production environments. Existing approaches to serve interoperability through standardized interfaces are limited by proprietary data exchange protocols and information models.Within industrial manufacturing and automation, standardization attempts between these systems are primarily focused on industrial interfaces like OPC/OPC-UA. However, the aggregation of data created by devices like sensors or machinery control units into useful information has not been satisfactorily solved yet as their underlying models are carried out using different modeling paradigms and programming languages, thus intercommunication is difficult to implement and to maintain.In this work, an integration chain for data from field level to top-level information systems is presented. As Manufacturing Execution Systems or Enterprise Resource Planning tools are implemented in higher programming languages, the modeling of field level information has to be adapted in terms of a semantic interpretation. The approach provides integration capabilities for OPC-conform data generated on the field level. The information is extracted from low level information systems, transformed according to object-oriented programming paradigms and object-relational standards and finally integrated into databases that allow full semantic annotation and interpretation compatible to a common information model. Hence, users on management levels of the enterprise are able to perform holistic data treatment and data exploration along with personalized information views based on this central data storage by means of a reliable and comfortable data acquisition. This increases the quality of data and of the decision support itself, as more time remains for the actual task of data evaluation.

A Cloud-based Approach for Maintenance of Machine Tools and Equipment Based on Shop-floor Monitoring

Maintenance and its cost continue, over the years, to draw the attention of production management since the unplanned failures decrease the reliability of the system and also the return of investments. Advanced maintenance techniques that capture and process shop-floor information can reduce costs and increase the sustainability of an enterprise. This paper presents a condition-based preventive maintenance approach integrated into a machine monitoring framework. The latter acquires data from shop-floor machine tools and analyses them through an information fusion technique to support the condition-based preventive maintenance operations. The proposed approach is developed into a software service, deployed on a Cloud environment. The service gathers and processes data, such as their actual processing time and machining time per tool, related to the operation of machine tools and equipment and calculates the expected remaining useful life of components. Moreover, it provides notifications to machine tool operators and maintenance departments, as well as it enables the communication among them using mobile technology. The framework is applied to a case study with data obtained from a machining SME.

Multi-agent based real-time production scheduling method for radio frequency identification enabled ubiquitous shopfloor environment

The lack of timely feedback shopfloor information during manufacturing execution stage leads to significant difficulties in achieving real-time production scheduling. To address this problem, an overall architecture of multi-agent based real-time production scheduling is presented to close the loop of production planning and control. Several contributions are significant. Firstly, wireless devices such as radio frequency identification (RFID) are deployed into value-adding points in a ubiquitous shopfloor environment to form Machine Agent for the collection and processing of real-time shopfloor data. Secondly, Capability Evaluation Agent is designed to optimally assign the tasks to the involved machines at the process planning stage based on the real-time utilization ration of each machine. The third contribution is a Real-time Scheduling Agent for manufacturing tasks scheduling/re-scheduling strategy and methods according to the real-time feedback. Fourthly, a Process Monitor Agent model is designed for tracking and tracing the manufacturing execution based on a critical event structure. Finally, a case is used to demonstrate the proposed multi-agent based real-time production scheduling models and methods.

Modular Configuration of an RFID-based Hybrid Control Architecture for a Situational Shop Floor Control

Nowadays, producing companies act in a turbulent environment, which is caused by the globalization of the economy and the continuous shift from seller markets to buyer markets. One central aspect is the demand for customized products at short delivery times and reasonable costs. In this context, shop floor control becomes more and more important and therefore, the complexity of its purposes increases. However, current shop floor information, which is indispensable for a targeted execution of these purposes, is often not available. The RFID (Radio Frequency Identification) technology enables an adequate and situational shop floor control. Since the integration and capabilities of RFID depends on specific framework conditions (e.g. forms of organization), an approach for a modular configuration of an RFID-based hybrid control architecture, that separates control efforts into centralized and decentralized control elements, is motivated. Finally, this approach could be implemented to a use case of a German automotive seat supplier.

Production and lead time quotation under imperfect shop floor information

We study the value of shop floor information for a manufacturer that operates under a make-to-stock queue scheme and quotes lead times to arriving customers. Two settings are analyzed where in the first setting the manufacturer is able to perfectly track the shop floor status, and in the second setting the manufacturer makes decisions under imperfect information. Under imperfect information, the problem is modeled as a Partially Observable Markov Decision Process. In the computational analysis, first the impact of information distortion on the policies is analyzed and it is shown that the increased likeliness of observing the true status of the system does not necessarily lead to higher profit. Further numerical analysis shows that as the inaccuracy in the data (range of error) increases, the value of information increases. The value of information is likely to be higher under high holding cost and low traffic. Then, the effect of Make-to-Order (MTO) and Make-to-Stock (MTS) queue schemes, as well as the effect of different lead time quotation schemes on the value of information are evaluated. Under MTO queue scheme shop floor information is more valuable under high traffic intensity, whereas under MTS queue scheme information is more valuable under lower intensity. Finally, the analysis reveals that if a firm quotes more precise lead times, then the need for actual shop floor information increases.

MULTI-AGENT-BASED COOPERATIVE COEVOLUTIONARY MODEL FOR DYNAMIC SHOP FLOOR RECONFIGURATION CONSIDERING PROCESS PLANNING

In order to react to volatile market demand and uncertain production objectives, distributed manufacturing resources have to be dynamically configured. However, the dynamics of process planning and shop floor information makes shop floor reconfiguration a challenging problem. The shortcomings of the existing research on shop floor reconfiguration are first discussed. Then a multi-agent-based framework for dynamic shop floor reconfiguration is presented, and a mathematical programming model taking process planning into consideration is constructed as well. To coordinate the resource assignment among agents, a cooperative coevolutionary algorithm is also put forward to find the optimal solution of the reconfiguration model. The advantages of the proposed model are using combined multi-agent and mathematical programming method to decompose and optimize the problem of reconfiguration and considering alternative process plans. Furthermore, a prototype system for dynamic shop reconfiguration is developed. The results of this research will help solve the problem of shop floor reconfiguration with complex and dynamic interactive structure.

A new approach for integrating process planning with scheduling

Integrated process planning with scheduling is a core activity in the manufacturing chain. Modern manufacturing processes require higher flexibility and capability of supporting distributed activities. In this paper, a novel STEP-NC Compliant Process Planning and Scheduling Algorithm (STEP-NCPPSA) is proposed to meet such requirements. The STEP-NCPPSA utilises STEP-NC compliant data models to represent the related manufacturing information. STEP-NCPPSA aims to achieve an Integrated, Intelligent, Informative and Interoperable (I4) manufacturing in a distributed manufacturing environment. Three phases, STEP-NC initial process planning, initial bidding, and Tree-based Genetic Algorithm optimisation are naturally integrated by the supporting STEP-NC concepts. STEP-NCPPSA is also capable of handling shop-floor information and re-process planning and scheduling to adapt to shop floor changes.

Analysis on Meaning and Current Research of Holonic Manufacturing Execution Systems

Systematic analysis is made on meaning and current research of Holonic Manufacturing Execution Systems (HMES). Characteristics of HMES are pointed out. It lies in the distributed structure and distributed decision-making mechanism come from holon, as well as the essence of being a shopfloor management information system. Papers on HMES are analyzed from three aspects: control framework construction, development framework and implementation. Control framework construction is the main research direction. Most of the frameworks are built on PROSA, and concentrated with emphasis on real-time scheduling on the manufacturing execution process to gain an optimized solution when faced random disturbance. As opposed to traditional legacy Manufacturing Execution Systems (MES) and framework MES, HMES has certain superiority, implementation and application of HMES also have good prospect. But because of the limitation of distributed decision-making mechanism, practical application has certain difficulty, which leads to the research work relatively slow.

The use and impact of technology in factory environments: evidence from a survey of manufacturing industry in Spain

The aim of this paper is to examine information related to the implementation of shop floor technologies and information technologies. This will be complemented with data relating to different levels of usage of the technologies. In addition, we test whether implementation alone is able to improve company performance or whether a high level of usage is also important. The empirical evidence comes from a sample of 151 Spanish manufacturing companies surveyed according to the European Manufacturing Survey's methods in 2006. Our results show that the most widely adopted technology is computer-aided design (CAD), followed by enterprise resource planning (ERP) and industrial robots. When the focus is on the level of use, the most highly used technologies turn out to be very similar—CAD–computer-aided manufacturing, ERP, and industrial robots—. Multiple regression analysis shows a positive correlation between the variable “level of usage” and performance. The relationship between adoption and results is less strong. These results have some implications and the paper ends with an explanation of how these findings should be used by firms in the development of future policies or strategic plans.

Data exchange strategy for manufacturing simulation of shop floor information systems

Manufacturing provides one of the most important applications of simulation. Standard interfaces could make information sharing effective, and hence promote the utilisation of simulators. An information model, which represents machine shop data and facilitates data sharing among machine shop's manufacturing execution system, scheduling system, and simulation system, has been developed at the National Institute of Standards and Technology. This paper discusses information exchange, using the information model, between different representations, presents an algorithm to exchange data between a database system and an eXtensible Markup Language (XML) document, and describes interfaces for XML schema's validation, structured query, and data transfer.

A closed-loop control architecture for CAM accounting for shop floor uncertainties

The primary focus of this paper is to demonstrate an enhanced closed-loop computer-aided manufacturing (CAM) architecture using a Petri net based analysis mechanism, which incorporates shop floor uncertainties to generate process plans and alternative processing sequences under dynamic conditions such as machine failures. Modern CAM software provide efficient, error-free, and user-friendly interfaces to develop processing sequences for manufacturing tasks. However, their effective scope is still limited from the post-process planning stage to the pre-machining stage. These types of software fail to incorporate the variability encountered in an actual shop floor to develop effective process plans. This is caused due to CAM software’s limitations in input handling mechanisms, limited simulation functionality, and inability to handle complex process variability from the shop floor. In this paper, CAM functionality is augmented with Petri net models to capture alternative process plans and shop floor variability arising due to equipment failures, repairs, and setups. The output from the analysis of the Petri net model provides a better understanding of the process characteristics and provides information to the CAM system to adapt to shop floor variability. The resulting information from the Petri net model allows the CAM system to compare alternative process plans while taking shop floor information into account. This mechanism can result in better decisions, reduced processing times, and better overall resource utilization, and provide alternative process plans based on current resource information.

Application of improved production activity control architecture for shop floor information system in digital manufacturing

Shop floor control (SFC) is responsible for the coordination and control of the manufacturing physical and information flow within the shop floor in the manufacturing system. Weaknesses of the production activity control (PAC) architecture of the shop floor are addressed by the Maglica's new system architecture. This architecture gives rise to unlimited number of movers and producers thus evolving more complex but decentralized architecture. Beijing Institute of Technology - production activity control (BIT-PAC) architecture introduces an idea of sub-producers and sub-movers thus reducing the complexity of the architecture. All the equipments including sub-producers and sub-movers are considered to be passive in the proposed shop floor information system. The dissemination of information from sub-producers and sub-movers is done manually through a PC. Proposed BIT-PAC SFC architecture facilitates the information flow from shop floor to the other area of the organization. Effective use of internet information services (IIS) and SQL2000 is done along with the ASP.NET technology to implement the application logic. Applicability of the software based on BIT-PAC architecture is checked by running application software on a network PC that supports the dynamic flow of information from sub-producers and sub-movers to the other parts of the organization. Use of software is also shown at the end for BIT training workshop thus supporting the use of SFC architecture for similar kind of environments.

Developing a Data Model of Product Manufacturing Flow for an IC Packaging WIP System

The IC packaging industry heavily relies on shop floor information, necessitating the development of a model to flexibly define shop floor information and timely handle manufacturing data. This study presents a novel data model of product manufacturing flow to define shop floor information to effectively respond to accelerated developments in IC package industry. The proposed data model consists of four modules: operation template setup, general process setup, enhanced bill of manufacture (EBOMfr) setup, and work‐order process setup. The data model can flexibly define the required shop floor information and decision rules for shop floor product manufacturing flow, allowing one to easily adopt changes of the product and on the shop floor. However, to handle floor dynamics of the ICD packaging industry, this work also proposes a WIP (i.e. work‐in‐process) system for monitoring and controlling the product manufacturing flow on the shop floor. The WIP system integrates the data model with a WIP execution module. Furthermore, an illustrative example, the MIRL WIP System, developed by Mechanical Industrial Research Laboratories of Industrial Technology Research Institute, demonstrates the effectiveness of the proposed model.

The optimization of attribute selection in decision tree-based production control systems

This study develops a learning-based production control system (PCS) to support a manufacturing system to make on-line decisions that are robust in the face of various production requirements. Selecting essential system attributes (or features) based on various production requirements to construct PCS knowledge bases is a critical issue because of the existence of a large amount of shop floor information in a manufacturing system. However, a classical decision tree (DT) learning approach to construct dynamic dispatching knowledge bases does not consider the optimal subset of system attributes in the problem domain. To resolve this problem, this study develops a hybrid genetic algorithm/decision tree (GA/DT) approach for DT-based PCS. The hybrid GA/DT approach is used to simultaneously evolve an optimal subset of system attributes and determine learning parameters of the DT from a large set of candidate manufacturing system attributes according to various performance measures. For a given feature subset and learning parameters of a DT decoded by a GA, a DT was applied to evaluate the fitness in the GA process and to generate the PCS knowledge base. The results demonstrate that the proposed GA/DT-based PCS has, according to various performance criteria, a better long term system performance than those obtained with classical DT-based PCS and the heuristic individual dispatching rules, according to various performance criteria.