Cycle Time Performance Research Articles

Green Supply Chain Performance Analysis of Cowhide Crackers Industry

Cowhide crackers Small and Medium-sized Enterprises (SMEs) process beef skin crackers as a home-based business. However, their supply chain faces challenges due to unstructured activities. Waste management, particularly cowhide and used water disposal, is inefficient. Research aims to evaluate performance indicators, measure green supply chain performance, and assess supply chain maturity. The methods employed include Analytical Hierarchy Process (AHP), Green Supply Chain Operation Reference (GSCOR), and Process Maturity Model (PMM). Results indicate a green supply chain management score of 58.901, with an average performance level influencing a maturity model value of 3.95. This places supply chain performance in the “managed and measurable” category. Three indicators, including recyclable percentage, cycle time, and environmental performance standards, have values below 50, necessitating improvement proposals. The research highlights areas for enhancement to enhance efficiency and sustainability in the cowhide crackers SMEs’ supply chain, crucial for long-term success and environmental responsibility.

Real-time production scheduling using a deep reinforcement learning-based multi-agent approach

In the real-time scheduling (RTS) research field, it has been shown that employing multiple dispatching rules (MDRs) for the components in a flexible manufacturing system will improve production performance much more than a single dispatching rule (SDR). To fulfill the goal of Industry 4.0 in production control and improve production performance, this study deploys a deep reinforcement learning-based multi-agent (DRLBMA) approach for real-time scheduling. The proposed approach uses the MDRs strategy by integrating two main methodologies: an off-line learning module and a Deep Q-learning-based multi-agent module. The proposed method employs a two-level self-organizing map (SOM) to determine the system’s states. The proposed methodology determines the best MDRs decision. The approach is applied to a case study of a smart manufacturing system. The results of the proposed method are compared to different scheduling strategies, such as reinforcement learning (RL)-based real-time scheduling, two-level self-organized map (SOM), and continuous rescheduling using a single dispatching rule, such as earliest due date (EDD), shortest processing time (SPT), and longest processing time (LPT). The findings reveal that, in terms of the total weighted tardiness, throughput, and mean cycle time performance criteria, the proposed DRLBMA-based real-time scheduling is more efficient than these scheduling strategies.

Problems and Solution Methods of Machine Scheduling in Semiconductor Manufacturing Operations: A Survey

Machine scheduling problems associated with semiconductor manufacturing operations (SMOs) are one of the major research topics in the scheduling literature. Lots of papers have dealt with different variants of SMOs’ scheduling problems, which are generally difficult to tackle theoretically and computationally. In this paper, the single machine, parallel machines, flow shops, and job shops scheduling problems from SMOs have been reviewed, based on different processing constraints, e.g., batch processing, auxiliary resources, incompatible job families, and reentrant flow, etc., with the cycle time, flow time, and throughput-related performance measures. Given the vast and diverse nature of the current literature, it is urgently needed to make a systematic survey in order to identify the important research problems, research trends, and the progress of the related solution methods, as well as clarify future research perspectives. We hope the findings and observations could provide some insights to the researchers and practitioners in this domain.

The impact of using a cloud supply chain on organizational performance

PurposeThis study aims to indicate the advantages of using cloud computing services, including the ways in which firms use cloud-based services to achieve accessibility, better communication, flexibility and effective provision of services. However, little evidence has been obtained related to the effectiveness of applying cloud computing services to supply management chains.Design/methodology/approachIn this study, a sample of 223 top 1,000 manufacturing firms in Taiwan that had implemented cloud-based supply chain management systems (CSCMs) was surveyed to determine what kind of internal resources in these companies were allocated to this implementation effort, how collaborative relationships were established in the existing supply chain to help make the transitions successful, how well their systems are working now that they have been implemented and whether these new systems have improved cycle time performance and the overall performance of their organizations. The study also examines the interrelationships among these variables.FindingsThe results reveal that, from the perspective of the managers who were surveyed, an effective allocation of internal organizational resources does have a positive, strong effect on external CSCM conditions. They also showed that when the relationship between internal and external resources is well constructed, the result is that CSCM improves supply chain management cycle time performance, which, in turn, leads to positive organizational performance.Originality/valueThe study reports some useful insights from the managers of CSCM systems related to how the execution of CSCM solutions can improve cycle time and organizational performance by enhancing internal organizational management and joint collaboration among supply chain partners. The findings from this survey will be useful to managers who are considering creating cloud-based supply management systems in the future.

Eligibility of BPMN Models for Business Process Redesign

Business process redesign (BPR) is an organizational initiative for achieving competitive multi-faceted advantages regarding business processes, in terms of cycle time, quality, cost, customer satisfaction and other critical performance metrics. In spite of the fact that BPR tools and methodologies are increasingly being adopted, process innovation efforts have proven ineffective in delivering the expected outcome. This paper investigates the eligibility of BPMN process models towards the application of redesign methods inspired by data-flow communities. In previous work, the transformation of a business process model to a directed acyclic graph (DAG) has yielded notable optimization results for determining average performance of process executions consisting of ad-hoc processes. Still, the utilization encountered drawbacks due to a lack of input specification, complexity assessment and normalization of the BPMN model and application to more generic business process cases. This paper presents an assessment mechanism that measures the eligibility of a BPMN model and its capability to be effectively transformed to a DAG and be further subjected to data-centric workflow optimization methods. The proposed mechanism evaluates the model type, complexity metrics, normalization and optimization capability of candidate process models, while at the same time allowing users to set their desired complexity thresholds. An indicative example is used to demonstrate the assessment phases and to illustrate the usability of the proposed mechanism towards the advancement and facilitation of the optimization phase. Finally, the authors review BPMN models from both an SOA-based business process design (BPD) repository and relevant literature and assess their eligibility.

Performance evaluation of the remanufacturing system prone to random failure and repair

ABSTRACTImplementation of new environmental legislation and public awareness has increased the responsibility of manufacturers. Remanufacturing has been applied in many industries and sectors since its introduction. However, only 10% to 20% of the returned products pass through the remanufacturing process, and the remaining products are disposed in the landfills. Uncertainties like high failure rates of the servers, buffer capacities, and inappropriate preventive maintenance policies would be responsible for most of the delays in remanufacturing operations. In this paper, a simulation-based experimental methodology is used to determine the optimal preventive maintenance frequency and buffer allocation in a remanufacturing line. Moreover, an estimated relationship between preventive maintenance frequency and Mean Time Between Failure (MTBF), is presented to determine the best preventive maintenance frequency. The solution approach is applied to computer remanufacturing industry. Analysis of variance (ANOVA), and regression analysis are performed to denote the most influential factors to remanufacturing cycle time (performance measures). A case study is used to show the applicability of the modelling approach in assessing and improving the cycle time, and the profit of a remanufacturing line . Managerial insights are highlighted to support managers and decision-makers in their quest for more efficient and smooth operation of the remanufacturing system.

Cycle Time Improvement of EtherCAT Networks with Embedded Linux-Based Master

We improve the cycle time performance of EtherCAT networks with embedded Linux-based master by developing a Linux Ethernet driver optimized for EtherCAT operation. The Ethernet driver is developed to establish a direct interface between the master module and Ethernet controllers of embedded systems by removing the involvement of Linux network stack and the New API (NAPI) of standard Ethernet drivers. Consequently, it is achieved that the time-consuming memory copy operations are reduced and the process of EtherCAT frames is accelerated. In order to demonstrate the effect of the developed Ethernet driver, we set up EtherCAT networks composed of an embedded Linux-based master and commercial off-the-shelf slaves, and the experimental results confirm that the cycle time performance is significantly improved.

Non-collision trajectories of service industrial robots

The innovative algorithm for robot collision testing was developed and debugged for programming industrial robots handling production and peripheral devices in a flexible manufacturing system. Due to this it allows the analysis of the robot effector and robot transition paths with the possibility of optimizing them in relation to the economy of the handling cycle, runway length, safety and operator time and overall handling performance. The key part of our proposal is to analyze the 3D model and its interpretation in a relevant form to enable data processing with modern computer graphics techniques with hardware support of calculations and work at the level of individual objects and polygons. Formalization of the robot's direct and inverse kinematic structure allows control of its interaction during servicing movements with other robot devices and peripherals. This ensures the optimal and unobtrusive trajectory of each mechanical element of the industrial robot serving the production and peripheral devices in the intelligent system.

Assessing Study Start-up Practices, Performance, and Perceptions Among Sponsors and Contract Research Organizations.

Site identification, site selection, and study start-up have become the focus of improvement by organizations conducting clinical trials. To examine and measure the process from site identification through site activation, Tufts Center for the Study of Drug Development (CSDD) conducted a comprehensive survey among pharmaceutical organizations, biotech companies, and contract research organizations (CROs). Responses from over 400 unique companies were gathered and analyzed. The results indicate that the start-up process is on average 5 to 6 months in total duration, and cycle times across all activities, including site identification, site selection, and study start-up, are faster for repeat sites than for new sites. Comparisons between sponsor and CROs indicate that CROs completed all site-related activities 6 to 11 weeks faster than sponsors. Other areas impacting cycle times were examined, including centralized versus decentralized functions, investment in technology, and organizational strategies that improve cycle time efficiency and performance. Tufts CSDD will explore this area in future research to gather additional insights into other factors that may be associated with speed and efficiency.

Analysis of Waste-Rock Transportation Process Performance in an Open-Pit Mine Based on Statistical Analysis of Cycle Times Data

In this paper, the performance of a waste rock transportation process in an open pit mine was assessed by using cycle time data. A computerized truck-excavator dispatch system was used to record the cycle times. The process was broken into seven steps (or components of the total cycle), durations of which were recorded for a period of 1 month, leading to N = 60,690 data points or dispatches. The open pit mine studied consisted of 12 waste types loaded by 14 excavators and hauled by 49 trucks (at a trucks-to-excavator ratio of 3.5:1) in 75 changing locations. The string-type data was coded using integers to allow a FORTRAN code to extract process performance parameters using statistical analysis. The study established a wide range of parameters including: the waste material generation rate (about 1.73 million t/month, 81% comprising waste rock), truck fill factor, f, total cycle time (Tct), production capacity, theoretical cycle time, non-productive cycle time Tnp, and cycle time performance ratio (CTPR), denoted as Tpr. The factors affecting the process performance include: truck model, excavator model, location (haul distance and road conditions) and material type. For a fixed material type and tonnage, the PDFs of the cycle time components were logarithmic in nature, capable of differentiating performance variations under different factors. It was concluded that the performance of the waste material transportation system in this mine was determined to be acceptable due to mean value of Tpr = 2.432 being closer to unity. Reduction measures were suggested to minimize the cycle time for the process bottlenecks determined from Pareto analysis (that is, full haul, empty haul and loading processes).

THE IMPORTANCE OF INTER-TEMPORAL INTEGRATION IN NEW PRODUCT DEVELOPMENT

According to the knowledge-based view (KBV), knowledge is a valuable resource that can lead to a competitive advantage. However, in industries where codified knowledge is used in developing successive iterations of products, codified knowledge has the potential to become obsolete over time and thus can also be an impediment to innovation. Using cycle-time (competitor comparison) as a performance measure, we find that inter-temporal integration — organisational practices designed to transfer tacit knowledge between former and current employees in successive new product development projects (NPDS) — enables a firm to effectively utilize codified knowledge to enhance product development cycle-time performance. Furthermore, using dysfunctional design change frequency as a performance measure, we find that inter-temporal integration has a negative relationship to this variable, but the relationship is stronger when knowledge codification is high. The results provide evidence of an important boundary condition to the benefit of codified knowledge in new product innovation.

Effect of upstream re-sequencing in controlling cycle time performance of batch processors

This paper demonstrates the effect of incorporating upstream sequence decisions in the cycle time control of batch processors. The focus is on dynamic control of a batch processor where near-future arrival information is available by predicting the process times on its upstream processor. In a particular decision point, the dynamic control task is to decide whether to start the batch process with one of the available product types immediately or to wait for future arrivals coming from the upstream processor. While considering a wait decision alternative, a re-sequencing approach at the upstream processor is proposed to shorten the arrival time of the desired product. Combining this architecture with a rolling horizon decision making, we propose a new look-ahead batch control strategy. A serial-batch processor system that is typical in wafer fabrication is modeled to demonstrate the approach. Simulation based benchmarking shows promising results.

Improving cycle time performance: the role of market turbulence and cultural competitiveness

Supply chains are getting increasing substance but the antecedents of their failure and success are not clearly identified till yet. The main aim of this study is to examine the influence of Cultural Competitiveness (CC), Market Turbulence (MT), and Knowledge Development (KD) on the performance of cycle time. The conceptual framework is proposed based upon extensive literature review. For this study, data was collected from 91 respondent manufacturing organizations. Upon assuring the reliability and validity of the constructs, correlation and hierarchical regression were used to test the hypotheses. Findings reveal that CC and MT have positive impact on cycle time. KD has insignificant association with performance of cycle time. No joint relationship of CC and KD, MT and CC, and MT and KD was found affecting the performance of cycle time. Practically, it is difficult to achieve dramatic reorientation of supply chains, and it is less likely that the failure of the two elements (CC and MT) can be quickly remedied. Our results indicate that such businesses can benefit from building CC – with the focus on MT – it will ensure that the company has at least some of the advantages of reducing cycle time.

The Effect of Single Rater Bias in Multi‐Stakeholder Research: A Methodological Evaluation of Buyer‐Supplier Relationships

As the global competitive landscape intensifies, firms have looked to their supply chain organizations to improve cost, visibility, and cycle time performance across functions, products, and markets. As a result, the scope of supply chain related operations have increasingly cut across organizational boundaries. To understand and capture such cross‐organizational activities, researchers have broadened the focus of their studies and included multiple stakeholders in their analysis (e.g., integration, sustainability, and buyer‐supplier relationships). However, multi‐stakeholder research has also increased the complexity and effort required to conduct studies across organizational boundaries. Unfortunately, many studies that use multi‐stakeholder constructs fail to fully address their multi‐sided nature during both construct conceptualization and data collection. Several studies suggest that neglecting the multi‐sided nature of certain constructs can affect the research validity and reliability and may invalidate research inferences and results, although such concerns have not been empirically demonstrated. The current study addresses this gap by performing a series of tests using data from 105 matched pairs of buyers and their suppliers to illustrate key methodological considerations for conducting multi‐stakeholder research. This study also offers practical guidance regarding assumptions routinely made in single rater research and proposes when single rater data may be appropriate for multi‐stakeholder research.

Impact of Recipe Restrictions on Photolithography Toolsets in an ASIC Fabrication Environment

In this paper, a detailed discrete event simulation model is used to better understand the effects of recipe constraints resulting from process restrictions and tool capabilities on overall average cycle time performance of a photolithography area and on average cycle times of individual mask layers. The study is motivated by the industry, in which engineers have to frequently make decisions on tool qualifications and recipe coverage. An experimental procedure is developed and implemented to show the impact of different levels of tool paths on photolithography toolsets. The simulation results show that increasing the number of tool paths decreases the overall average photolithography cycle time for particular wafer loading levels. Also, as start volumes increase, toolset utilizations increase and the impact of single-path tools on average cycle times increases. Immature processes and low-use processes tend to have more single paths and thus suffer higher average cycle times accordingly. Furthermore, it is reported that average cycle time decreases significantly under multiple process environments due to the lower impact of single paths.

Probability-Based Prediction of Degrading Dynamic Systems

This paper presents a methodology to provide the cumulative failure distribution (CDF) for degrading, uncertain, and dynamic systems. The uniqueness and novelty of the methodology is that long service time over which degradation occurs has been augmented with much shorter cycle time over which there is uncertainty in the system dynamics due to uncertain design variables. The significance of the proposed methodology is that it sets the foundation for setting realistic life-cycle management policies for dynamic systems. The methodology first replaces the implicit mechanistic model with a simple explicit meta-model with the help of design of experiments and singular value decomposition, then transforms the dynamic, time variant, probabilistic problem into a sequence of time invariant steady-state probability problems using cycle-time performance measures and discrete service time, and finally, builds the CDF as the summation of the incremental service-time failure probabilities over the planned life time. For multiple failure modes and multiple discrete service times, set theory establishes a sequence of true incremental failure regions. A practical implementation of the theory requires only two contiguous service-times. Probabilities may be evaluated by any convenient method, such as Monte Carlo and the first-order reliability method. Error analysis provides ways to control errors with regards to probability calculations and meta-model fitting. A case study of a common servo-control mechanism shows that the new methodology is sufficiently fast for design purposes and sufficiently accurate for engineering applications.

The Relationship between Cash-To-Cash Cycle Time and Financial Performance of Manufacturing and Wholesale/Retail Companies in Korea by Using Multiple Linear Regression Analysis

The Relationship between Cash-To-Cash Cycle Time and Financial Performance of Manufacturing and Wholesale/Retail Companies in Korea by Using Multiple Linear Regression Analysis

Cost and cycle time reduction in the service industry: a field study of insurance claims operation

The issues of cycle time management and cost reduction in the service industry are the concerns of the empirical study presented in this paper. In specific, we study the claims handling process which is one of the most essential and critical functions of an insurance company. The objective of our study is to gain an understanding of the impact of various operational decisions, such as assignment of claims to claims analysts, choice of claims handling method and involvement of an attorney on the cycle time and cost performance of claims operation. The field study presented in this paper was conducted at a major insurance company where we collected and analysed a large dataset on claims characteristics, cost, cycle time and operational decisions of claims handling process. The paper identifies the important claim characteristics that drive the cost and cycle time performance in settling a claim and concludes with a discussion on the managerial implications of the field study.

The Impact of NPD Strategy, Product Strategy, and NPD Processes on Perceived Cycle Time

Studies of new product development (NPD) have identified a variety of factors that influence cycle time, but most of these findings are based on case studies of individual firms. The few empirical studies that have attempted to examine the generalizability of these findings have tended to focus on one set of decisions (e.g., product strategy decisions) without considering the impact of organizational variables. To address this gap in the literature, this paper examines the impact on perceived cycle time of six variables that reflect a business unit's NPD strategy, NPD environment, product strategy, and NPD processes. The study also examines whether the impact of each of these antecedent variables is independent of the remaining variables. Contingency theory implies that cycle time performance will reflect the internal consistency of multiple contingencies and multiple structural characteristics. This implication is tested by evaluating the incremental explanatory power of two distance variables: one based on a theoretically defined ideal profile; and a second based on an empirically defined ideal profile. This analysis is important, because it permits a test of the proposition that understanding the pattern of contextual and structural variables adds additional insight to the understanding of cycle time performance. The analysis, based on data collected from 164 firms, indicates that the development of a formal NPD strategy, the creation of an appropriate climate for innovation, and the use of cross‐functional teams all contributed to improved perceptions of satisfactory cycle times. It was also found that executives in business units with broad product lines were less likely to perceive their cycle times as satisfactory. Contrary to expectations, an increasing emphasis on products involving breakthrough core processes was found to increase perceptions of satisfactory cycle times. Moreover, the use of heavyweight project managers had no significant impact on cycle time perceptions. The study also found no evidence to indicate that deviations from either a theoretically or an empirically defined ideal profile lengthen perceived cycle time.

An analysis of the ceiling height requirement for a large-scale semiconductor fab

This paper proposes the proposition that the fab ceiling height may become a bottleneck for throughput in a large-scale semiconductor fab. To justify the proposition, we propose a systematic approach for the design of the fab ceiling height. In this approach, we develop a queuing network model to evaluate the cycle time performance of a fab design under a target throughput. This queuing network model is adapted from Connor et al. [1996. A queueing network model for semiconductor manufacturing. IEEE Transactions on Semiconductor Manufacturing, 9 (3), 412–427] by additionally treating the transportation facilities as finite-capacity resources. Numerical experiments were carried out. The results indicate that a large-scale fab with an inappropriate ceiling height may limit the installation of transportation capacity, which, in turn, limits the utilisation of tool capacity, and thus lowers the fab throughput that can be achieved.