The purpose of this paper was to use the Overall Equipment Effectiveness productivity formula in plant manufacturing and convert it to measuring productivity for forklifts. Productivity for a forklift was defined as being available and picking up and moving containers at port locations in Seattle and Alaska. This research uses performance measures in plant manufacturing and applies them to mobile equipment in order to establish the most effective means of analyzing reliability and productivity. Using the Internet of Things to collect data on fifteen forklift trucks in three different locations, this data was then analyzed over a six-month period to rank the forklifts’ productivity from 1 – 15 using the Operating Equipment Effectiveness formula (OPEE). This ranking was compared to the industry standard for utilization to demonstrate how this approach would yield a better performance analysis and provide a more accurate tool for operations managers to manage their fleets of equipment than current methods. This analysis was shared with a fleet operations manager, and his feedback indicated there would be considerable value to analyzing his operations using this process. The results of this research identified key areas for improvement in equipment reliability and the need for additional operator training on the proper use of machines and provided insights into equipment operations in remote locations to managers who had not visited or evaluated those locations on-site.

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Master’s thesis is concerned with maintenance management in manufacturing companies focusing on TPM. The first part of the thesis deals with the topic theoretically and proposes possible solution in company Siemens Electric Machines s.r.o. based on system analysis. The practical part then describes the current state of maintenance management and recommend various measures to improve autonomous, scheduled and reactive maintenance in this company.

Orientador: Aneirson Francisco da Silva / Resumo: A gestão baseada no Lean Manufacturing tem como princípio o desenvolvimento de processos enxutos com a capacidade de utilizar da melhor forma os recursos disponíveis e eliminar atividades que não agregam valor. Com isso, o programa Total Productive Maintenance (TPM), está entre os métodos que auxiliam nesse objetivo, pois desenvolve a função de gerir a manutenção de máquinas, equipamentos e meio ambiente de trabalho de forma que os investimentos feitos tendam ao aumento da eficiência global. Para isso, uma maneira de controlar o desempenho dos processos é aplicando ferramentas capazes de mensurar a eficiência relativa. Pois, além de verificar quantitativamente a eficiência relativa, estes métodos e ferramentas servem de fundamentação para auxiliar os gestores na tomada de decisões nas organizações. A empresa em estudo, uma multinacional de autopeças situada no Vale do Paraíba/SP, emprega o programa TPM e apoia-se no indicador Overall Equipment Effectiveness (OEE) para as avaliações de eficiência. Entretanto, o presente estudo propôs um indicador de eficiência que combina um modelo multicritério com a Lógica dos Conjuntos Fuzzy, no qual, diferentemente do OEE, é possível escolher os parâmetros que interferem na eficiência do processo e adicionar o conhecimento dos especialistas aos dados nítidos para assim, verificar o comportamento do cenário. Para o indicador proposto, foram simulados três cenários, dispostos em forma de ranking (do mais eficiente ao menos eficiente) e compa... (Resumo completo, clicar acesso eletrônico abaixo) / Abstract: Management based on Lean Manufacturing has as principle the development of lean processes with the ability to make the best use of available resources and eliminate activities that do not add value. Thus, the Total Productive Maintenance (TPM) program is one of the methods that help this goal, because it develops the role of managing the maintenance of machinery, equipment and working environment, for that the investments made tend to increase the overall efficiency. For this, one way to control process performance is to apply tools developed to measure relative efficiency. Because, in addition to quantitatively verifying relative efficiency, these methods and tools are based managers for decision-making in organizations. The company under study, an auto parts multinational located in Vale do Paraíba / SP, use the TPM program and for efficiency assessments is supported by the Overall Equipment Effectiveness (OEE) indicator. However, the present study proposed an efficiency indicator that combines a multicriteria model with the Fuzzy Set Logic, in which, unlike OEE, it is possible to choose the parameters that interfere in the process efficiency and to add expert knowledge to the clear data for verify the behavior of the scenario. For the proposed indicator, three scenarios were simulated, creating the ranking (from the most efficient to the least efficient) and compared to the OEE indicator ranking. Once this was done, it was observed that there was divergence in most positio... (Complete abstract click electronic access below) / Mestre

半導體相關產業的發展是支撐我國在世界經濟體系中佔有重要地位的主要原因之一，而其中尤以半導體產品的製造與代工備受矚目。近年來半導體相關產業的發展呈現成長狀態，連帶引發半導體製造廠之產能呈現供不應求的現象，因此如何作好產能管理，使能盡量符合顧客需求，便成為管理當局關注的議題。 半導體製造廠的產能管理著重在機台設備面，此與本產業之多數製程係仰賴精密機台之功能有關。為了探討如何充份利用設備產能，故本研究從成本動因的角度，探討可能影響機台設備產能的因素。 由於半導體相關產品種類繁多，功能各有不同，因此在接受顧客訂製時亦呈現多樣化現象。當半導體產品之設計不同時，將衍生複雜性之問題，可能對機台設備效率發生影響，因此本研究之研究問題一即在探討產品複雜性對設備效率之影響為何。 此外，為求品質方面的優異、加快研發產品的問世速度，以及排程上的適切，許多相關作業活動和作業型態因應而生，使整體生產作業之複雜性提高，而生產作業複雜性是否成為影響設備效率之因素，即為本研究之研究問題二欲探討的內容。 在半導體製造廠之幾近全自動化的生產作業環境中，機台設備除了具有製程上的能力外，其自動化的運作方式是否會對效率面發生影響，亦為本研究有興趣的主題；由於機台設備之自動化運作設計有助生產周期縮短及浪費現象減少，為增加效率之來源，即為效率動因的定義，因此形成本研究之研究問題三探討的內容，即效率動因(機台的自動化運作時間)對設備效率之影響。 本研究透過田野研究及文獻探討形成三項主要假設： 1.產品複雜性與設備效率存在負相關： 當產品之製程技術等級愈高，表示產品愈複雜，導致設備效率愈差。 2.生產作業複雜性與設備效率存在負相關： 當品質各項作業、研發相關作業和小批量作業數量愈多，影響正常生產愈大，使生產情況愈複雜，導致設備效率愈差。 3.效率動因與設備效率存在正相關： 當機台設備之自動化運作時間愈多，表示各項操作作業愈單純，可使設備效率愈好。 本研究採取田野(Field)及田野實證(Field Empirical)研究方式。為了使學術界對半導體製造產業有更多瞭解，因此本研究先從事田野研究，由筆者在民國88年9月至民國89年6月，每週親自至個案公司1-3天，以觀察、閱讀公司內部資料和訪談的方式進行對此產業的瞭解。接著以個案公司之民國89年1-3月的機台設備日資料為樣本，進行設備綜合效率(OEE)之實證迴歸分析，並佐以DEA敏感性分析結果以為驗證。 設備綜合效率(OEE)之實證迴歸分析結果顯示：生產作業複雜性對設備效率確實有負向影響，且自動化效率動因對設備效率有正向影響。在(DEA)敏感性分析結果方面，生產作業複雜性對設備效率確實有負向影響，且自動化效率動因對設備效率有正向影響。 此項研究結果的隱含意義在於： 一、概括而論，由品質作業、研發作業和批量水準構成的生產作業複雜性確實對機台設備效率有負向影響，因此管理當局應著重於品質鑑定作業、品質內部失敗作業、研發相關作業和未滿載批次作業之管理。 二、由機台設備之自動化運作時間構成的效率動因對機台設備具有正向影響，因此在實務運作上，各相關部門在進行作業設計時應考慮此點，而當機台設備運作異常時，設備工程師等人員應充分展現支援的能力，使之盡速恢復自動化運作狀態。 由於OEE及DEA兩個迴歸模型所驗證的結果大致上相同，故本研究之結果應具可信度。 根據實證研究結果，本研究對實務界的建議為： 1.建議實務界可繼續針對各種功能性不同的機台設備群組作效率影響因素分析，有助管理與控制導致不同設備效率損失的影響因素，且可利用DEA方法以彌補OEE效率評估之缺失，俾能取得更有意義的參照結果。 2.DEA的實證結果顯示品質作業中的事前維修保養作業似有助設備效率之提升，與OEE之實證研究結果不同，建議管理當局可以告知製造部人員關於DEA的實證結果，則製造部人員應更能體認到品質的預防作業之重要性，同時亦建議個案公司可繼續進行事前維修保養作業對設備效率之影響研究。 3.未滿載批次之批量水準對設備效率有不利影響，建議個案公司儘量避免，利用併貨方式處理之。但若真的無法併貨時，則亦應考慮各機台設備之產能利用狀況，盡量分配給負擔較輕的機台進行製造作業，以減少瓶項機台的發生機率。 本研究對學術界的建議為： 1.對各種不同功能性的設備而言，若能取得影響其效率的產品複雜性因素，則可幫助實務界進行產品設計和設備產能分配之決策，本研究未達成此目的，建議後續研究者可繼續為之。 2.建議後續研究者可以針對本研究採用之效率動因觀念，積極地找出會使設備效率提升的因素為何，作為引導員工行為的依據。 3.不論學術界或實務界欲採用DEA方法來評估生產效率時，皆應謹慎選擇投入和產出項目，否則容易得到錯誤的引導。 / The development of semiconductor industry, especially the semiconductor manufacturing and foundry, is one of the main contributors that win Taiwan worldwide attention and upgrade the rank of Taiwan’s competitive advantage. In recent years, the continuous growth of semiconductor industry has brought about shortage of supply. Therefore, how to manage production capacity effectively and to meet market needs has become a critical management issue. The focus of capacity management in fab is on manufacturing equipment, because it is the equipment that makes manufacturing activities work. In order to study how to fully utilize equipment, this research emphasizes searching for the influencing factors for equipment efficiency in semiconductor manufacturing, which is often measured by OEE. Those factors are designed as product complexity, process complexity, and efficiency drivers. Based on theoretical foundation, this study comes out three hypotheses as follows: 1. Product complexity negatively influences equipment efficiency. 2. Process complexity negatively influences equipment efficiency. 3. Efficiency driver positively influences equipment efficiency. (Efficiency driver is not clear for me here) The research proceeds with two methods: field study and field empirical study. For the former, observation, document reading and interview techniques are adopted one to three days a week, from September 1999 to June 2000. As to the latter, daily data from one semiconductor manufacturing fab are collected. The sample size is 4382. Two analyses are done: one is specified by OEE and the other is by DEA, which is for sensitivity analysis. The empirical results of both analyses indicate that process complexity and efficiency driver empirically has significant negative and positive effects on equipment efficiency respectively. The results support two hypotheses of this study. The empirical results suggest that: 1. In general, process complexity in terms of quality, R&D and batching activities has negative influence on equipment efficiency. Therefore, the management should make efforts on managing the monitor and test, internal failure, R&D and batching activities. 2. The auto-operation status can help enhance equipment efficiency, and thus should be taken into account when designing all the relevant activities. Besides, it should be emphasized if any out-of-order status are confronted, all supporting personnel, such as equipment engineers, should try as soon as possible to get equipment repaired and restored to work automatically. Results from sensitivity analysis arrive at roughly the same conclusions. Therefore, this research should be reliable and valid, and the findings can be possibly good reference for the management in semiconductor industry and future researchers.)

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The purpose of this thesis is to implement Total Productive Maintenance (TPM) in Nigeria Plastics Manufacturing Company. Manufacturing companies round the world pay huge amount of money for purchasing new equipments to boost their production however nothing or little is done to achieve or obtain full output from the machine for which it is intended to do. Small losses in time or deviations from planned or calculated capability are taken as usual machine performance. But currently as a result of improved capability levels and demand of quality product at lower prices, purchasing latest machine/equipment is not a way out unless it is completely used. Total Productive Maintenance (TPM) is a method that involve everybody totally, from high management to all workers to implement a complete maintenance program for all machine/equipment during its life. This method ends up in most effectiveness of tools, equipment, virtuously improved workers, tidy up working area, neat and clean working environment. A structure is going to be developed with the potential of evaluating the impact of implementing total productive maintenance within. By evaluating the result or outcome of Total Productive Maintenance (TPM), manufacturing companies can create sensible/smart decisions to improve the potency and standard of the machine, equipment and also the product on XYZ Plastics Manufacturing Company in Nigerian.

The design process of a production system referred to as the production system design process (PSDP) impacts on the operational performancethroughout the lifecycle of the production system, especially on the rampupand operation phases. Despite the impact of activities of PSDP on the operational performance, how to manage the PSDP is still a challenge for manufacturing companies. Earlier research urged to develop a systematic PSDP concerning its impact on the operational performance. This thesis aims to contribute with knowledge of how manufacturingcompanies can manage the PSDP by investigating 1) the enablers in thePSDP that impact on operational performance in ramp-up and operation phases, and 2) how the lean production concept could be adopted tomanage the activities during the PSDP. A case study was conducted in aprocess type manufacturing company, where empirical data were collectedfrom three new production line launching projects by qualitative means. This thesis identifies a set of enablers in the PSDP that potentiallyimpact the operational performance after launching the productionsystem. Empirical findings demonstrate that ensuring proper actions onthe identified enablers in the PSDP could lead to higher operationalperformance of the designed production system. These enablers rangefrom the company´s internal boundary to external vendors, requiring asystematic way to manage these diverse aspects. Adopting the lean production concept in the PSDP context, this thesis proposes a model of Lean Production System Design Process, containing 13 principles andrelevant practices. The proposed model of lean PSDP could be used as a systematic processto manage the activities in the PSDP that would ensure proper actions related to the identified enablers. Empirical findings indicate that adoptionof lean in the PSDP could result in reducing lead time of launching a new production system, and achieving fast ramp-up and desired operational performance considering sustainability aspects. Finally, this thesis demonstrates how the lean PSDP could be a means to achieve a sustainable competitive advantage based on the resource based view theoretical perspective. / Utformningsprocessen av ett produktionssystem, i denna avhandlingkallad produktionssystemets utformningsprocess (PSUP), påverkar denoperativa prestandan under hela produktionssystemets livscykel, särskilt iupprampnings- och driftsfasen. Traditionellt sett ligger fokus underutformningsprocessen på att lansera det nya produktionssystemet vidplanerad tidpunkt och enligt budget. Trots att de aktiviteter somgenomförs i utformningsprocessen påverkar den operativa prestandan idriftsfasen, ägnas ofta mindre uppmärksamhet åt designfasen än vad somvore önskvärt. Tidigare forskning har argumenterat för att utveckla ensystematisk designprocess för framtagning av produktionssystem medsyfte att nå en positiv påverkan på den operativa prestandan. Forskningen i denna avhandling bidrar till att öka kunskapen om hurPSUP kan hanteras och förbättras genom att identifiera: 1) möjliggörare i PSUP som påverkar den operativa prestandan i upprampnings- ochdriftfasen, och 2) hur lean konceptet skulle kunna användas för att hanteraaktiviteterna under PSUP. Resultatet är identifieringen av ett antal faktorer/möjliggörare iproduktionssystemets utformningsprocess (PSUP) som potentiellt kanpåverka den operativa prestandan efter lansering av produktionssystemetoch produktionsstart. Dessa möjliggörare handlar om alltifrån frånföretagets interna gränser till externa leverantörer och kräver ensystematisk procedur för att dra nytta av faktorernas potential. Genom attanvända lean även i PSUP-sammanhanget, föreslås här konceptet Lean PSUP (produktionssystemsutformningsprocess), som innehåller 13 principer och relevanta praxis. Den föreslagna modellen för lean PSUP skulle kunna användas och gestruktur till hanteringen av aktiviteterna i utformningsprocessen.Forskningen indikerar att lean inte bara kan användas i driftsfasen utanäven i utformningen av ett produktionssystem, vilket skulle kunnaresultera i bättre integration mellan olika funktioner, minska ledtiden förutformning och lansering av ett nytt produktionssystem, och uppnå snabbupprampning och önskad operativ prestanda, både avseende produktionoch hållbarhet. Slutligen visar denna avhandling hur lean PSUP kan varaett sätt att uppnå konkurrensfördelar ur ett resursbaserat teoretiskt perspektiv.

The manufacturing industry is competitive and is constantly striving to improve OEE. In the transition to smart production, digital technologies such as IIoT are highlighted as important. IIoT platforms enable real-time monitoring. In this sense, digital technologies such as IIoT are expected to improve OEE by enabling the analysis of real-time data and production availability.  A qualitative study with an abductive approach has been conducted. The empirical material has been collected through a case study of a heavy-duty vehicle industry and the theoretical framework is based on a literature study. Lastly, a thematic analysis has been used for the derivation of appropriate themes for analysis. The study concluded that challenges and enablers related to the implementation of IIoT to improve OEE can be divided into technical and cultural factors. Technical challenges and enablers mainly consider the achievement of interoperability, compatibility, and cyber security, while cultural factors revolve around digital acceptance, competence, encouragement of digital curiosity, and creating knowledge and understanding towards OEE. Lastly, conclusions can be drawn that implementation of IIoT has a positive effect on OEE since it ensures consistent and accurate data, which lies a solid foundation for production decisions. Also, digitalization of production enhances lean practices which are considered a key element for improving OEE.