A Simulation Environment to Support Prognostics and Health Management in Smart Manufacturing Systems

Abstract

Maintenance activities are a significant part of an advanced manufacturer's budget and could potentially represent an organization's source of vulnerability in sustaining a stable supply chain. It is crucial for a manufacturer to understand the implications of maintenance on their organization's ability to produce quality products in an e cient time-frame at an acceptable cost. Furthermore, it can be expensive, time consuming, and create a risk to finished product supply to evaluate results from altering maintenance activities and policies during a production cycle. This is especially true when attempting to implement prognostics and health management (PHM) methods on existing smart manufacturing systems (SMS). This thesis presents research studying the trade-o↵s of various maintenance policies, including PHM methods, using a simulation with the purpose of providing decision support. The modeling approach involves building the structure for a simulation in which maintenance policies, probabilistic models of failure rates, processing speeds, and costs are inputs into the simulation environment. This generality allows for quickly altering a manufacturing model, and the ability to consider novel policies where control of machine parameters is needed. The outputs of the simulation evaluate policies in terms of cost per unit produced and overall equipment e↵ectiveness (OEE), a widely used industry metric.Data from industrial partners was used in the validation of the simulation environment. This work is part of a larger attempt to equip plant managers and business leaders with the methods for understanding which PHM strategy is best suited for their manufacturing system. i

An integrated Machine Learning Model for Manufacturing industry

“…Regrettably, the accuracy of class descriptions learnt using IREP is frequently worse than that of class descriptions learned using the C4.5 rules method [1], a rule-inducing variation of C4.5. [18] described various changes to IREP aimed at increasing its accuracy, including a different rule-evaluation criterion, a different stopping condition, and a postprocessing optimization operation, resulting in the method RIPPER. He demonstrated that RIPPER is error rate competitive with C4.5 regulations and retains the efficiency of IREP.…”

“…algorithms were used to just-in-time manufacturing systems. To begin, neural network models and decision trees were employed to determine the quantity of kanbans in a dynamic JIT production lines [18]. The quantity of kanbans is critical to the efficient running of a JIT manufacturing system.…”

“…The findings established that the methodologies used may extract data to aid in intelligent decision making in industry. Other applications include developing decision rules for conceptual design of steel members subjected to bending [17], diagnosing engine faults [18], detecting manufacturing defects in disk drives [19], diagnosing motor pumps [8], analyzing non-destructive testing of spotweld quality [29], managing and controlling raw material procurement, and accelerating rotogravure printing.…”

Politik Kooptasi Karaeng Terhadap Hak Pilih Buruh Tani Pada Pilkada Serentak Tahun 2015 Di Kabupaten Bulukumba

“…Seorang pengikut seringkali juga terlibat dalam perselisihan, karena telah melakukan pelanggaran atau karena dia merasa dirugikan oleh seseorang, maka dia akan melaporkan masalhnya tersebut kepada Karaeng. 8 Persoalan perbedaan kedudukan antara Bangsawan dan orang biasa, atau pelapisan sosial yang berlaku dalam masyarakat Sulawesi-Selatan, perhatian perlu kita arahkan pada soal wujud sistem tersebut serta bagaimana orang menciptakannya. Artinya, kriteria apa yang dipakai oleh masyarakat Sulawesi-Selatan, terutama dalam masyarakat Makassar dan Bugis, kaum Bangsawan dikenal dengan gelar Karaeng atau aru'yang diartikan sebagai 'Raja' sedangkan kerabat-kerabatnya atau keturunannya desebut anakaraeng atau anakarung.…”

“…Artinya, kriteria apa yang dipakai oleh masyarakat Sulawesi-Selatan, terutama dalam masyarakat Makassar dan Bugis, kaum Bangsawan dikenal dengan gelar Karaeng atau aru'yang diartikan sebagai 'Raja' sedangkan kerabat-kerabatnya atau keturunannya desebut anakaraeng atau anakarung. 9 Mengingat pembicaraan menyangkut masyarakat yang hidup dari bertani, maka perbedaan yang dicari tentunya yang berhubungan dengan soal kepemilikan tanah. Penentuan tanah sebagai ukuran ternyata sesuai dengan pandangan masyarakat di sana mengenai apa yang dimaksud dengan kaya, seperti tampak dikalangan Karaeng.…”