Shop Floor Decision Research Articles

Dynamic project planning with digital twin

The digital twin (DT) concept plays a crucial role in Industry 4.0 and the digitalization of manufacturing processes. A DT is a virtual representation of a physical object, system, or process, designed to accurately reflect its real-world counterpart. In manufacturing, existing process data are often incomplete and do not qualify as a DT. However, with the help of specialized communication frameworks and cheaper, easier-to-use sensors, it is possible to integrate the existing manufacturing execution system (MES) and enterprise resource planning (ERP) data with the missing data gathered from the shop floor to create a comprehensive DT. In this paper, we present a digital shop floor decision support system (DSS) for non-linear aluminum manufacturing production. The system is split into five main components: digitization of shop floor orders; merging and sorting of MES, ERP, and shop floor data; custom and genetic optimization algorithms for the aging furnace production step; layout construction mechanism for optimal placement and stacking of orders in the furnace; and a user-friendly graphical user interface (GUI). The system’s performance was evaluated through three tests. The first test measured the efficiency of digitization, the second aimed to quantify time saved in finding packets in the hall, and the last test measured the impact of the optimizer on furnace productivity. The results revealed a 23.5% improvement in furnace capacity, but limitations were identified due to usability and human intervention.

On process modelling of cold chamber die casting of Al alloy by using buckingham’s Π approach

In the present study, outcome of Taguchi based model has been used for mathematical modelling of Al alloy cast component weight (W) by using Buckingham’s π approach in cold chamber (CC) die casting process. During mass production of CC die casting components, W measurement is used as one of the yardstick to ensure defect free casting. Three input parameters namely 1st phase pressure (Pr1); 2nd phase pressure (Pr2); and limit switch (LS) position were selected to give output in form of cast component W based upon Taguchi design. The macro model based upon Taguchi design has been further used for micro modelling of W in CC die casting using Buckingham’s Π approach in form of mathematical equation. It was observed that ratio of die opening time for maximum W (Wmax) to minimum W (Wmin) was 1.06. This study provides main effects of Pr1, Pr2 and LS variables on casting ‘W’ and shed light on controlling the casting defects in CC die casting process for shop floor decisions. The comparison with experimental results has been made for further validation of model.

MANUFACTURING INDUSTRY JOB SHOP FLOOR DECISIONS THROUGH HYBRID GENETIC ALGORITHM

This article addresses flexible manufacturing system (FMS) Performance is likely to improve with employment of various resources efficiently. Initially simultaneous scheduling problems are solved by means of priority rules like first come first serve (FCFS), shortest processing time (SPT) and longest processing time (LPT) to find out the operational completion time for 120 problems. Later gene rearrangement genetic algorithm (HGA) is implemented for same set of problems with makespan as objective and the results are compared with the results of priority rules. The results are performed well by using HGA. The same HGA is used to find the finest optimal sequence that minimize the operational completion time.

PREFAB Framework - PRoduct quality towards zEro deFects for melAmine surface Boards industry

Abstract Zero Defects is one of the ultimate targets for manufacturing quality control and assurance. Such systems are becoming common in advanced manufacturing industries but are at an initial stage in more traditional industrial sectors, such as wood panels, laminates production, pulp and paper processing and composite panels production. This paper proposes the PREFAB framework, applied to the wood-based panels industry, to minimize rejected products using AI, machine learning and IoT devices. The framework was built through action research with a Portuguese wood-based panel manufacturing. This framework delivered an innovative decision support system that provides relevant and timely recommendations for shopfloor decision making and to support process/product engineering.

A unified index for proactive shop floor control

Unpredictability of performance under the influence of various uncertainties makes decision-making a complex task on the shop floor. A measure which can indicate the expected shop floor scenario over a projected timeline can be an effective hands-on tool for a shop floor decision maker. The current work proposes three measures, namely complexity, penalty, and desirability of a shop floor situation and aggregates them into a single unified index (UI). Given an indicative list of uncertainties and the prevailing shop floor situation, a periodic simulation approach is presented to observe the changes in the UI. The extent of change in the UI, both in terms of magnitude and direction, is used to identify those significant environmental variables which need intervention. Developing a proactive control measure from the perspective of a decision maker on the shop floor, demonstration of CRITIC (Criteria Importance through Intercriteria Correlation)-based automated decision-making mechanism in a manufacturing setup and a simulation approach to aid the decision-making process are the highlights of the current work. The results reported are with reference to a high-pressure die casting unit.

Solving the Dynamic Job Shop Scheduling Problem using Bottleneck and Intelligent Agents based on Genetic Algorithm

The problem of Dynamic Job Shop (DJS) scheduling is one of the most complex problems of machine scheduling. This problem is one of NP-Hard problems for solving which numerous heuristic and metaheuristic methods have so far been presented. Genetic Algorithms (GA) are one of these methods which are successfully applied to these problems. In these approaches, of course, better quality of solutions, avoiding premature convergence, and robustness of solutions is still among the challenging arguments and in the researchers’ center of attention. The investigations in real manufacturing environments indicate that many of these systems have Bottleneck Recourses (BR). According to the concepts of the Theory of Constraint (TOC), the output of manufacturing systems is limited based on BR capacity. Hence, for improving system performance, one must find and investigate the improvement of BR effects in different levels of decision-making. Moreover, the capacity of these resources should be improved to the maximum possible limit. In this study, for detecting and using BR in shop floor decisions (e.g. scheduling), a new detection method of bottleneck for DJS problems known as bottleneck detection method based on Taguchi Approach (TA-DJS) has been developed. On the other hand, the adapting of GA operators in amount and range of coverage can operate as an efficient approach in improving its operation and effectiveness. In this way, the adapting for operators prevents its premature convergence and the adapting in the range of coverage causes maximum use of the problem’s important resources and better performance of the algorithm in each step of its run. In the proposed GA (GAIA), initially the adapting in the amount of algorithm’s operators based on the solutions’ tangent rate for premature convergence is done, then the adapting in the range of coverage of operators’ algorithm, in first step, happens by operators convergence on BR (which was detected initially) and, in the next step, occurs by operators convergence on the elite solutions so that the search process focuses on more probable ranges than the whole range of solution. Comparing the problem results in the static state with the results of other available methods in the literature indicated high efficiency of the proposed method.

A Complexity Based Look-ahead Mechanism for Shop Floor Decision Making

Manufacturing Complexity has been extensively reported in the literature in the ways it can be classified, modelled, assessed and measured. However, the use of complexity measures for shop floor decision making has not been studied exhaustively. The paper demonstrates the use of a complexity measure for shop floor decision making. Knowledge of the transition of shop floor complexity into undesirability can give a correct indicative for any decision maker to intervene and take the necessary corrective actions to bring the system back to its desirable state. The current paper presents an information-theoretic approach based model which considers production scheduling, maintenance and quality functions simultaneously to come up with a complexity quantifier for a shop floor. At any point in time, various environmental factors like machine failures, corrective maintenance time variability, due date alteration, process shifts etc. are simulated into the future and their effect on the job states both in terms of schedule and quality are observed. The probability of these state occurrences is then quantified as complexity of situation which is subsequently scaled to a penalty based “undesirability index”. The complexity is re-evaluated every time a fresh event occurs, thus enabling the decision maker to be more predictive about the future state of the system and in turn, the performance of each of the manufacturing functions. Thus, the model so developed, deploys a complexity based look-ahead mechanism for identifying undesirable state transitions. The novelty of the work lies in the way it has been developed keeping the perspective of a shop floor manager in view and also in the way it can be readily used for decision making.

Real-time information capturing and integration framework of the internet of manufacturing things

Currently, the typical challenges that manufacturing enterprises faced are the lack of timely, accurate and consistent information of manufacturing things (resources) during manufacturing execution. Real-time information visibility and traceability allows decision makers to make better-informed shop-floor decisions. In this article, a real-time information capturing and integration architecture of the internet of manufacturing things (IoMT) is presented to provide a new paradigm by extending the techniques of IoT to manufacturing field. Under this architecture and its key components, the manufacturing things such as operators, machines, pallets, materials etc. can be embedded with sensors, they can interact with each other. Considering the challenges of processing a huge amount of real-time data into useful information and exchange it among the heterogeneous application systems, a Real-time Manufacturing Information Integration Service (RTMIIS) has been designed to achieve seamless dual-way connectivity and interoperability among enterprise layer, workshop floor layer and machine layer. Finally, a near-life scenario has been used to illustrate the proof-of-concept application of the proposed IoMT.

Application of ORFPM system for lean implementation: an industrial case study

This paper presents an on-line radio frequency identification (RFID)-based facility performance monitoring (ORFPM) system. This system supports the implementation of Lean production in a small manufacturing facility. This system uses wireless monitoring via RFID to automatically generate a real-time value stream map (VSM) using computer-aided programming. Creating the VSM automatically saves time, reduces errors, and makes the VSM more visible to supervisors at any time. This up-to-date information allows supervisors to make more accurate, real-time shop floor decisions. The results of this study indicate that the ORFPM system can successfully track performance variations when production has low time consumption requirements and is labor intensive. Several Lean improvement suggestions are also proposed based on the collected data from the ORFPM system.

Event-driven multi-agent ubiquitous manufacturing execution platform for shop floor work-in-progress management

It has been reported that radio frequency identification (RFID) technology is applied to manufacturing shop floors for capturing and collecting real-time field data. Real-time information visibility and traceability allows decision makers to make better-informed shop floor decisions. It has been a great challenge to process a huge amount of RFID data into useful information for managerial uses. This paper presents an event-driven shop floor work-in-progress (WIP) management platform for creating a ubiquitous manufacturing (UM) environment. The platform aims to monitor and control dynamic production and material handling through RFID-enabled traceability and visibility of shop floor manufacturing processes. The platform provides facilities to process shop floor real-time RFID events and to aggregate actionable and meaningful operational information to support decision-making activities. An information processing mechanism based on a critical event model is proposed to organise real-time field data in various abstract levels for enterprise decisions. A case study at an air conditioner manufacturing company is used to demonstrate how the proposed platform can benefit its shop floor WIP management by showing how production and logistic operators and their supervisors accomplish their tasks.

High Performance Work Practices and Employee Voice: A Comparison of Japanese and Korean Workers

Using a unique new cross-national survey of Japanese and Korean workers, we report the first systematic evidence on the effects on employee voice of High Performance Work Practices (HPWPs) from the two economies which are noted for the wide use of HPWPs. We find for both nations that: (i) workers in firms with HPWPs aimed at creating opportunities for employees to get involved (such as shopfloor committees and small group activities) are indeed more likely to have stronger senses of influence and voice on shopfloor decision making than other workers; (ii) workers whose pay is tied to firm performance are more likely to have a stake in firm performance and hence demand such influence and voice; and (iii) consequently workers in firms with HPWPs are more likely to make frequent suggestions for productivity increase and quality improvement. As such, this paper contributes to a small yet growing new empirical literature which tries to understand the actual process and mechanism through which HPWPs lead to better enterprise performance.

Establishing production service system and information collaboration platform for mold and die products

This paper investigates how the new concept of product service systems can be used and extended to transform, elevate, and revitalize traditional equipment manufacturing industry such as the Mold and Die (MD) sector. A mold and die production service systems (MPSS) framework is established based on recent developments within our industrial collaborators. Within the MPSS framework, MD manufacturers become more specialized in producing MD products and components while sharing and outsourcing manufacturing-oriented services (MOS) from a service provider. Typical services include collaborative order pooling and release, collaborative project progress status tracking, contractor-managed collaborative outsourcing, collaborative product design, collaborative production planning and scheduling, and after-sales technical supports. MOSs are designed, developed, and deployed as SaaS (software as application services) following the service-oriented architecture. Collectively, they form iMPSS—an Information and Collaboration Platform that enables MPSS. The use of iMPSS leads to benefits for stakeholders involved in providing mold and die functionality including better shopfloor decisions and reduced IT investments.

High Performance Work Practices and Employee Voice: A Comparison of Japanese and Korean Workers

Using a unique new cross-national survey of Japanese and Korean workers, we report the first systematic evidence on the effects on employee voice of High Performance Work Practices (HPWPs) from the two economies which are noted for the wide use of HPWPs. We find for both nations that: (i) workers in firms with HPWPs aimed at creating opportunities for employees to get involved (such as shopfloor committees and small group activities) are indeed more likely to have stronger senses of influence and voice on shopfloor decision making than other workers; (ii) workers whose pay is tied to firm performance are more likely to have a stake in firm performance and hence demand such influence and voice; and (iii) consequently workers in firms with HPWPs are more likely to make frequent suggestions for productivity increase and quality improvement. As such, this paper contributes to a small yet growing new empirical literature which tries to understand the actual process and mechanism through which HPWPs lead to better enterprise performance.

Modeling a Management Accounting System for Lean Manufacturing Firms

Lean thinking is rapidly becoming the dominant paradigm in manufacturing. Traditional management accounting fails to provide relevant information to decision makers in a Lean organization. A relatively new management accounting approach better suited to supporting lean initiatives is emerging. Popularly termed Lean accounting (LA), the information generated by this system is portended to be simpler to prepare, easier for shop-floor decision makers to understand, and more useful for decision making. Although the advantages of this emerging management accounting paradigm are becoming more widely understood, a clear definition and theoretical basis is lacking. The purpose of this exploratory study is to identify some of the most critical characteristics of firms that have changed their accounting systems to support their lean production The SEM results from 259 U.S. survey respondents suggest that companies accounting for Lean operations with value stream costing (VSC) have the following characteristics: 1) top management that is highly supportive of change and lean initiatives; 2) workers who are trained in quality issues and empowered to make decisions; 3) considerable use of lean manufacturing tools such as reduced setup times, cellular manufacturing, 5S, Kanban, and Kaizen events; 4) information that is visual, aligned with strategic objectives, and readily available on the shop floor; 5) elimination of inventory tracking and allocation of labor and overhead; and 6) a simplified and streamlined management accounting system that is aligned with strategic goals. The analyses of these results suggest that accountants are beginning to understand the different types of informational needs of Lean environments.

A simulation-based decision support system The example of a furniture manufacturer

In this paper, we address a way to improve a classic kanban control system, by using kanban cards as an informational/decisional entity in order to enrich shop-floor information/decision. The real-time information collected and the simulation tool proposed enable to coordinate distributed decision according to a unique and global performance indicator. Our proposition consists in enabling any shop-floor decision maker to evaluate different kanban priority scenarios according to a unified objective, taking into account the global situation of the workshop. Models of the data collection and decision support system are presented. A generic information system enables to provide a relevant view of shop-floor status. Such information will be useful to efficiently feed a real-time simulation tool in order to evaluate solutions. The application is illustrated using the case of an industrial furniture manufacturer.

RFID-based wireless manufacturing for real-time management of job shop WIP inventories

Modern manufacturing shop-floors suffer from a bottleneck of capturing and collection of real-time field information. Paper-based manual systems are time-consuming, prone to errors, tedious, and frequently damaged, lost or misplaced. As a result, the information does not accurately and promptly reflect the real-life situations and changes of the situations due to disturbances. Without up-to-date information, it is impossible to make accurate shop-floor decisions. This paper presents an affordable approach to shop-floor performance improvement by using wireless manufacturing (WM)—an emerging advanced manufacturing technology (AMT). WM relies substantially on wireless devices such as RFID (radio frequency identification) or auto-ID sensors and wireless information networks for the collection and synchronization of the real-time field data from manufacturing workshops. Emphasis is placed upon how to deploy WM technology for managing work-in-progress (WIP) inventories in manufacturing job shops with typical functional layouts. This approach avoids the change from functional to cellular layouts in order to retain existing operational flexibility while improving efficiency and capacity. Representative WIP logistic processes will be used to demonstrate how production and logistic operators and their supervisors accomplish their tasks in a WM shop-floor.

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 impact of resource flexibility and staffing decisions on cellular and departmental shop performance

Shop floor control researchers have begun to compare the shop performance advantages of varying forms of resource flexibility. Two major streams of shop floor control research, dual resource constrained shop scheduling (DRC) and group technology (GT), are converging as the literature documents that different forms of resource flexibility aid shop performance in different ways. For example, the DRC literature shows that a small amount of worker flexibility, in the form of cross-training, may be all that is required for superior shop performance. However, the GT literature demonstrates that restricting machines from processing individual part families reduces overall shop effectiveness. Not only does it appear that diverse forms of resource flexibility may be used to alter shop performance in different ways, it may also be that environmental characteristics play a role in arbitrating the performance-improving strength of different forms of flexibility. Studies that have jointly investigated machine and labor flexibility have generated very different conclusions.In this paper we examine the performance advantages of machine and labor flexibility over a wide and realistic set of assumptions and shop floor decisions. We evaluate shop floor control within three different shop configurations at four different levels of staffing. Results indicate that the conclusions of previous studies regarding the choice between labor and machine flexibility are relatively insensitive to a group of labor assignment rules, somewhat more sensitive to changes in demand variability, and very sensitive to staffing levels. Further, this study demonstrates that under several sets of conditions, promoting labor flexibility to the exclusion of machine flexibility provides excellent performance.

Human resource management, trade unions and empowerment: two cases from India

This paper discusses the introduction of schemes aimed at employee empowerment within a context of strong industrial relations in India. The pressure put on profit margins by a competitive business environment is forcing an increasing number of Indian enterprises to view employee empowerment as a serious strategic option. Getting workers to take responsibility for shop-floor decisions over quality, safety, productivity and material use appears, at first sight, an alluring prospect. It would seem that men and women at the bottom of the pyramid cannot but be warmly appreciative of power-sharing arrangements from which they have something to gain, but there are forces at work which can actively obstruct or quietly subvert attempts at redistributing power. In this paper the focus is on some of the motives a trade union might have to do so.

A project-oriented production model of batch plants

This paper presents a project-oriented framework for interactive analysis of the feasible plans and schedules that can provide an effective/efficient flow of orders within a batch process. The proposed approach is based on a hierarchical project-oriented production model that integrates production planning with short-term scheduling and resource leveling. At the highest layer of the hierarchy, the use of aggregate activities and their milestone dates is aimed to emphasize a management perspective of the production model. As a core element of the model a process task network is used. Each node of this network is expanded further into sub-tasks and their detailed schedules. Efficiency in resource's usage during short-term scheduling is improved by changing process task durations. The implementation of the project-oriented production planning methodology has been based on the existing literature in project management (Leachman, 1982, Leachman, 1983; Hackman and Leachman, 1989), but many alternative techniques can be used for specific layers (sub-problems) of the proposed hierarchy. An attractive feature of the project oriented approach is that descentralized decision making is favored. Conflicts between management objectives and shop-floor decisions are solved iteratively in a two-tier scheme. Simple examples are considered to illustrate the potentials and advantages of the project-oriented approach.