Data-driven machine criticality assessment – maintenance decision support for increased productivity

Data-driven decision support for maintenance management is necessary for modern digitalized production systems. The data-driven approach enables analyzing the dynamic production system in realtime. Common problems within maintenance management are that maintenance decisions are experience-driven, narrow-focussed and static. Specifically, machine criticality assessment is a tool that is used in manufacturing companies to plan and prioritize maintenance activities. The maintenance problems are well exemplified by this tool in industrial practice. The tool is not trustworthy, seldomupdated and focuses on individual machines. Therefore, this paper aims at the development and validation of a framework for a data-driven machine criticality assessment tool. The tool supports prioritization and planning of maintenance decisions with a clear goal of increasing productivity. Four empirical cases were studied by employing a multiple case study methodology. The framework provides guidelines for maintenance decision-making by combining the Manufacturing Execution System (MES) and Computerized Maintenance Management System (CMMS) data with a systems perspective. The results show that by employing data-driven decision support within the maintenance organization, it can truly enable modern digitalized production systems to achieve higher levels of productivity

A comparative study between stapler and handsewn anastomosis in gastrointestinal surgeries in Coimbatore Medical College Hospital Coimbatore

BACKGROUND: Intestinal anastomosis dates back to 1000 BC, the era of Sushruta. ‘’The great Indian surgeon’’ he described the use of black ants during the suturing of intestinal anastamosis. Lembert then described his seromuscular suture technique in 1826 which became the mainstay of gastrointestinal anastomosis in the second half of the century. Currently the single layer extramucosal anastomosis is popular, advocated by Matheson of Aberdeen, as it probably causes the least tissue necrosis or luminal narrowing. The evaluation of mechanical sutures by means of stapler use has become a real technological advancement. AIM OF THE STUDY: 1. To compare the handsewn anastomosis and stapler anastomosis techniques. 2. To compare the time duration of surgery, hospital stay, restoration of functions and postoperative morbidity. MATERIALS AND METHODS: 50 Patients admitted in our ward and emergency department of surgery, Coimbatore medical college hospital during the period of June – 2016 to July 2017 will be allocated into two groups according to the type of anastomosis, handsewn and stapler. The handsewn anastomosis done by double layer, continuous suturing technique. Staplers used in anastamosis were linear cutting, linear non cutting, circular, curvilinear staplers. The parameters considered are time duration of surgery, hospital stay, post operative leak, restoration of gastrointestinal function, post operative morbidity. The anastomosis commonly done are gastro-jejunostomy anterior and posterior, jejuno-jejuostomy, ileo-colic, and colo-rectal anastomosis. RESULTS: Regarding the total duration of the anastomosis time, it is shorter in stapler group when compared to handsewn group. with significant predictive value. Appearance of bowel sounds and starting of oral feeds were earlier in stapler with significant predictive value. Total duration of the hospital stay was less in stapler group when compare with handsewn group. with statistically significant predictive value. Regarding complications stapler group had lesser complications when compared to hand sewn group. CONCLUSION: Stapler anastomsis reduced the duration of surgery,early postoperative recovery of bowl functions, and reduced postoperative hospital stay, lesser anastomotic leak than the conventional handsewn anastomosis. As per our study, stapler anastomosis has better outcome than conventional handsewn anastomosis

Machine criticality assessment for productivity improvement: Smart maintenance decision support

Purpose\ua0The purpose of this paper is to increase productivity through smart maintenance planning by including productivity as one of the objectives of the maintenance organization. Therefore, the goals of the paper are to investigate existing machine criticality assessment and identify components of the criticality assessment tool to increase productivity.Design/methodology/approach\ua0An embedded multiple case study research design was adopted in this paper. Six different cases were chosen from six different production sites operated by three multi-national manufacturing companies. Data collection was carried out in the form of interviews, focus groups and archival records. More than one source of data was collected in each of the cases. The cases included different production layouts such as machining, assembly and foundry, which ensured data variety.Findings\ua0The main finding of the paper is a deeper understanding of how manufacturing companies assess machine criticality and plan maintenance activities. The empirical findings showed that there is a lack of trust regarding existing criticality assessment tools. As a result, necessary changes within the maintenance organizations in order to increase productivity were identified. These are technological advancements, i.e. a dynamic and data-driven approach and organizational changes, i.e. approaching with a systems perspective when performing maintenance prioritization.Originality/value\ua0Machine criticality assessment studies are rare, especially empirical research. The originality of this paper lies in the empirical research conducted on smart maintenance planning for productivity improvement. In addition, identifying the components for machine criticality assessment is equally important for research and industries to efficient planning of maintenance activities

Real-Time data-driven average active period method for bottleneck detection

Prioritising improvement and maintenance activities is an important part of the production management and development process. Companies need to direct their efforts to the production constraints (bottlenecks) to achieve higher productivity. The first step is to identify the bottlenecks in the production system. A majority of the current bottleneck detection techniques can be classified into two categories, based on the methods used to develop the techniques: Analytical and simulation based. Analytical methods are difficult to use in more complex multi-stepped production systems, and simulation-based approaches are time-consuming and less flexible with regard to changes in the production system. This research paper introduces a real-Time, data-driven algorithm, which examines the average active period of the machines (the time when the machine is not waiting) to identify the bottlenecks based on real-Time shop floor data captured by Manufacturing Execution Systems (MES). The method utilises machine state information and the corresponding time stamps of those states as recorded by MES. The algorithm has been tested on a real-Time MES data set from a manufacturing company. The advantage of this algorithm is that it works for all kinds of production systems, including flow-oriented layouts and parallel-systems, and does not require a simulation model of the production system

Cyber-Physical Production Testbed: Literature Review and Concept Development

Many researchers use virtual and simulation-based testbed technology for research in production and maintenance optimization. Although, the virtual environment produces good results, it cannot imitate the unexpected changes that occur in actual production. There are very few physical testbeds emulating actual production environment. The aim of this paper is to present a concept of a cyber-physical production testbed based on review of Cyber-Physical Systems (CPS) testbeds in research. The testbed consists of a semi-automatic production line equipped with system monitoring tools, data analysis capabilities and commercial software. This testbed will be used for demonstration of data acquisition for production and maintenance prioritization. Additionally, the testbed will be used for research in IoT platforms for production optimization

Organisational Constraints in Data-driven Maintenance: a case study in the automotive industry

Technological development and innovations has been the focus of research in the field of smart maintenance, whereas there is less research regarding how maintenance organisations adapt the development. This case study focuses to understand what constraints maintenance organisations in the transition into applying more data-driven decisions in maintenance. This paper aims to emphasize the organisational challenges in data-driven maintenance, such as trustworthiness of data-driven decisions, data quality, management and competences. Through a case study at a global company in the automotive industry these challenges are highlighted and discussed through a questionnaire survey participated by 72 people and interviews with 7 people from the maintenance organisation

Common Fixed Point Theorems For (ϕ,F)- Integral Type Contractive Mapping On C^*-algebra Valued b-metrix Space

The object of this paper, we establish the concept of integral type of common fixed point theorem for new type of generalized -valued contractive mapping. The main theorem is an existence and uniqueness of common fixed-point theorems for self-mappings with -contractive conditions on complete -algebra valued -metric space. Moreover, some illustrated examples are also provided

An algorithm for data-driven shifting bottleneck detection

Manufacturing 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 average and the non-bottlenecks over a time interval. The algorithm has been tested over real-world MES data sets of two manufacturing companies, identifying the potentials and the prerequisites of the data-driven method. The main prerequisite of the proposed data-driven method is that all the states of the machine should be monitored by MES during the production run

MATRIX METALLOPROTEINASES 2 AND 9 IN AVOCATION OF MULTITUDINAL COMPLICATIONS IN EXPLICITLY TO CARCINOMA: REVIEW

Matrix metalloproteinases (MMPs) are a large group of calcium-dependent zinc containing endopeptidases which are mainly concerned with the remodeling of tissue along with degradation of the extracellular matrix. At the present scenario, there is knowledge of about 26 MMPs which are found to be highly regulated by the growth hormones, cytokines, etc., present within the body. At times of normal homeostasis, their levels within the body are low, and their number usually increases at times of pathological conditions. Its generation is known to occur from the pro-inflammatory cells and connective tissues. They may even lead to the process of apoptosis by its interactions with surface receptors. In the clinical trials sectors, various MMPs along with their inhibitors are examined to import the properties of being a high biomarker in the cancer diagnosis, antiangiogenic agents, various other disorders such as chronic allograft nephropathy, diabetic nephropathy, cardiovascular diseases, neuropathic pain, wound healing, angiogenesis processes, immune response, corneal ulceration, embryonic development, and nervous system disorders. As a result, enormous number of studies on this particular enzyme in the marking of cancer and their elevation in the above-mentioned diseases has to be carried out so that it would remain as a useful tool in their diagnosis. The present work is designed to emphasize the concise review of MMPs, in particularly MMP-2 and MMP-9 along with their variant roles, keeping in mind, that it would be advantageous for the researchers to bring out more promising results and to intensify diagnosis of various infirmities, especially in cancer.Keywords: Matrix metalloproteinase-2, Matrix metalloproteinase-9, Biomarker, Matrix metalloproteinases, Carcinoma, Extracellular matrix, Malignancy, Gelatinases, Tumor