Abstract: The pharmaceutical industry is inserted into a scene of fierce competition, facing rising costs of research and development and is subject to greater regulatory requirements. It is important that pharmaceutical companies seek to design, measure and improve the performance of its operations and of its equipment. The performance indicator named overall effectiveness of equipment (Overall Equipment Effectiveness -OEE) is often adopted to evaluate the performance of machines and production lines. The aim of this study is to evaluate the use of OEE as tool for performance evaluation, identification of losses and as a basis for the development of continuous improvement actions in a public national pharmaceutical laboratory. The results indicated that, although the OEE has been employed to measure the performance of an individual equipment, he made possible the identification of waste that impacted the production process as a whole. The OEE has allowed managers to prioritize actions directed to the Elimination of the main waste identified, being used as a tool to support the production management.
Keywords: Pharmaceutical industry; performance indicators; overall effectiveness of equipment; continuous improvement.
During the last two decades, the pharmaceutical industry showed significant growth, originating, inter alia, industrial concentration, high profits and combination of growth in consumption of medicinal products with price increase (Vargas et al., 2009). The world pharmaceutical market is highly concentrated. Although composed of a large number of companies, is controlled by some multinationals. Due to the complexity of processes and related knowledges, pharmaceutical companies do not manufacture all varieties of medicines, specializing in certain therapeutic classes, what characterizes the pharmaceutical industry as a differentiated oligopoly (Santos et pine, 2012). This sector has faced several challenges, as Herlant exposed (2010), among which:
A critical issue that contributes to the increase of the General costs of the sector, in addition to the P & D, is the rising cost of manufacture: for brand-name medications, that cost fluctuates between 27 and 30% of the value of sales (Basu et al., 2008). In this context, the pharmaceutical companies have sought to reevaluate their operations in search of greater operational efficiency. Practices used in automotive and electronics to reduce process times, eliminate waste and reduce costs have been adopted in pharmaceutical branch. Since 2004, an international benchmarking study called "Operational Excellence in the Pharmaceutical Industry" is conducted by the Institute of Technology Management (ITEM) of the University of St. Gallen, in Switzerland, which assesses the technical deployment of operational management in the pharmaceutical industry from the adoption of different established concepts of production management, as the Just in Time (JIT), Total Quality Management (TQM) and Total Productive Maintenance (TPM). Based on the experience of the most efficient, one of the main results of the survey pointed out that the first step to achieving operational excellence is the standardized and stable operation of the equipment (Friedli et Goetzfried, 2010).
One of the ways to standardize and stabilize the operation of the equipment is to plan and manage its use, in the context of a production system. The overall effectiveness of indicator equipment (Overall Equipment Effectiveness -OEE), originally employed in the automotive industry, is currently used in various industries to support the planning and management of the use of equipment, measuring, evenly and consistently, the factors that directly affect its performance (Ahuja et Khamba, 2008).
In a public pharmaceutical laboratory located in Rio de Janeiro, there was the need to quantify the productivity losses of equipment and develop actions to eliminate them, with a view to increasing the efficiency of the production system. This work seeks to show the importance of using the OEE as an instrument of management support, showing the results of your application in the lab in question, in particular, its use in the identification and quantification of waste, serving as a basis for the design of continuous improvement actions.
In the next section of this article, will be presented the concepts and calculations of the OEE. In the third section, will be described in the method adopted; and, in the following section, the assessment of the production flows for critical equipment. In the fifth section, will be discussed the implementation of the indicator; and on Friday, the results of the analysis of the OEE, including waste and the improvement actions identified. In the last section, will be presented for the completion of the work.
The OEE was proposed by Seiki Nakajima to track the progress of the TPM. The goal of the TPM is to achieve the maximum effectiveness of the equipment, resulting in the Elimination of faults, in the reduction of downtimes, switch, in the increase of productivity and improvement of quality (Ahuja et Khamba, 2008). The OEE is the product of three indexes (see equation 1):
These indexes quantify the six big losses that impact the operation of the equipment and which were identified by Nakajima. Loss or waste are defined as activities that absorb resources, but do not create value. In table 1, can be viewed the indexes and the losses which affect the rates in question.
Table 1. Relationship between losses and OEE indexes
|Indexes||Losses||Definition of losses|
|Availability||Breaks and crashes||Defect or abnormal condition that prevents the proper functioning of the equipment|
|Set ups and tweaks||Time for the exchange of machine and settings|
|Performance efficiency||Idleness and small stops||Short outages. Characterized by intermittent shutdowns.|
|Reduced speed||Actual speed lower than the theoretical speed|
|Quality rate||Defects in the process||Non-conforming units (defective) and rework|
|Losses relating to initial startup (startup) of the equipment||Reduction of the quantity of products in line according to the necessary adjustments to the machine reaches the condition of regime after a long stop period**Source:** Elaborated from Hansen (2006)|
|Type of set up||The average time of set up (h)||Time of return obtained with the use of the EET (h)||Reduction (%)|
As the coating step was the bottleneck of production lines for medicines, (B) and ©, reducing the time of preparation of the equipment has increased not only the capacity of the machine, but also the global flow capacity of the production lines of A, B and c. prior to implantation of the EET, every campaign of seven lots of product were spent, on average, 33.36 hours of set up. After the use of the tool, this time reduced to 9.27 hours, on average, every batch, 24.09 7 campaign hours for processing.
In total, the other most significant outage causes were: corrective maintenance and other stops. Outages resulting from corrective maintenance were its smaller than those caused by trade. However, the flaws become unstable equipment operation, and can increase processing time of lots and compromising the quality of the products. Reduced reliability of the machines contributes to the formation of in-process inventory and for the lack of adherence to the production scheduling (Friedli et Goetzfried, 2010).
Due to the likely correlation between equipment failures and the aspect of the product C, the coating on the equipment was stopped for checking the overall functioning of the machine. In this way, the necessary corrective maintenance was performed. It was observed that the failure caused by insufficient depression of the drum was due to the saturation of the exhaust filters, and weekly cleaning of these filters has been included in the preventive maintenance routines. As a result of this measure, there was no more records depression insufficient on the drum. During periods without production scheduling, preventive maintenance activities were carried out, however, there have been various types of defects in the equipment during the total period analyzed. This was due to the fact that part of the failures followed random patterns, were not failures whose occurrences were proportionate to the time of use of the equipment.
Preventive maintenance activities are based on an estimated probability that the machine will break down or fail within a specified interval of time. However, for some components, the likelihood of failure increases with the time of operation. In these cases, the maintenance based exclusively on operating time has no effect on the rate of failure. An action for the reduction of the number of random crashes is the implementation of more efficient methods of maintenance, such as predictive and proactive. This deployment would benefit the entire production system, since random faults are observed in equipment of all work centers. In the code of other stops, were pointed disruptions relating to cleaning validation routines (sampling, time to wait for results of analysis), the temporary operator offsets to other activities, waiting for documentation and follow-up carried out by the process service industry. The largest percentages of code 14 (other stops) in relation to the load time were observed between 9 and 12 and were due to the activities of cleaning validation.
Resuming the Pareto analysis, it appears that the other outages accounted for losses of little significant availability, since each percentage less than presented 5% of the total. For some of these outages, were recorded observations relevant to the establishment of future continuous improvement actions.
It was observed, for example, sometimes the activities of approval of intermediate product (physical-chemical analyses and records in batch documentation) delayed the start, due to the short time interval between the compression and coating and the non-existence of an iron Lung in product process.
All repairs carried out by the operator were due to correction of faults in spraying of pistols. By virtue of these notes, Maintenance checked the pistols and requested the purchase of new units.
The charts for lack of intermediary were not significant. However, during the time period analyzed, if reprogramming of the work centers, which reduced the incidence of this type of outage. The lack of adherence to the schedule and the consequent reprogramming were due to deviations of quality of raw materials, the equipment capacity constraints of the Department of quality control and procurement processes which are submitted the public laboratories pharmaceuticals. Law No. 8666, of 1993 (Brazil, 1993), which regulates the purchases of official laboratories provides that these must be carried out by means of bids, based on the criterion of the lowest price. The delay and the lack of flexibility of the bidding process (Hasenclever et al., 2008) aggravate in emergency cases, as, for example, when delays in supplies, Deprecations of raw materials and packaging materials and the need for purchases of parts for the repair of equipment outages. In these cases, production is interrupted for longer periods, and it is necessary to reprogram the work centers.
Observing the behavior of the performance efficiency index of equipment in Figure 4 d, there is a growing trend, with the exception of the month 11. This month, there were flaws in the inflation and deviations in the operation of the spray gun. It was noted the occurrence of lower temperatures of the air blown and lower rates of spraying. Consequently, coating times increased, reducing the efficiency ratio.
During the time period examined, there were no records of equipment operation interruptions for stops less than 5 minutes (small charts).
Were observed lots whose processing time went beyond the theoretical. Finishing times vary according to characteristics inherent in the process itself. At the finish, it is not always possible to use parameterization, which provides the lowest process time. Sometimes, the parameters need to be adjusted, impacting the operation time.
In the process, the operator monitors the aspect of the tablets and shall carry out the changes, if necessary. For example, if at the beginning of the coating the tablets are crumbly (that is, with low wear resistance by friction), the speed of rotation of the drum must be reduced in order to lower the risk of imperfections on the surface of the pills, since the parameters are interdependent. With the reduction of drum rotation, the flow of application of suspension should be decreased and/or the input air temperature must be increased, otherwise, the pills may be overly humid and, thus, some clinging to the other.
Air humidity fluctuations of entry can also change the coating and drying conditions, making it necessary to adjust the process variables (Pinto et Fernandes, 2001). As a result of these facts, is provided to the operator to change the parameters, since within the tracks specified in product development and validated. During the process, at regular intervals, the operator checks the average weight of the nuclei, and the application is terminated when the specified range to the coated tablets is reached. Even though the operators say that, in General, use the total amount of suspension, the end of the spraying is determined by the weight gain pills, allowing variations, albeit small, of the total volume of suspension applied and, consequently, the finish time.
Another factor that contributes to the oscillation of the process is the need for reheating of the nuclei, if any extended stops during the spraying of the suspension. After meals and shift change periods, or after the correction of deviations in the functioning of the equipment, the pills are heated again before continuing with the application of the coating film.
In the light of the foregoing, the action identified for improvement of this index has been the reduction of process variability sources that interfere in the finish time: equipment failures, the parameterization process, physical attributes of the intermediate product (such as the hardness and friability, that determine the mechanical strength of the pills during the coating) and total volume of sprayed suspension. To minimize the variability of the process, the institution can adopt statistical process control (SPC) and the design of experiments, methods that can be used for all processes, benefiting the production system as a whole.
In table 2, it can be shown a summary of the main waste and improvement actions identified based on use of the OEE.
Table 2: Summary of the main or detected improvement actions using the OEE
|OEE Index analyzed||Major waste Identified||Improvement actions||Status of Improvement Actions|
|Quality||Aspect of deviations detected in the product C||Adjustments in product coating parameters||Fulfilled|
|Check the general operation of the equipment because of possible correlation between failures and adjustments on the machine and the presence of appearance of deviations in pills||Fulfilled|
|Availability||Set up times||Use of EET||Fulfilled|
Activity included in the preventive maintenance routines (weekly cleaning of exhaust filters of equipment)
|Implementation of predictive and / or proactive maintenance to minimize random failures||Implementation to be evaluated|
|Other stops - mostly due to cleaning validation activities||No applicable improvement actions because the validation activities are not routine. The waste was eliminated with the completion of validation||Not applicable|
|Performance Efficiency||Higher processing time than theoretical processing||Implementation of SPC and design of experiments to reduce process variability that affects the operating time||Implementation to be evaluated|
Through this case study, confirmed that the OEE can be used as an instrument of support to the management of pharmaceutical production. In addition to measuring equipment performance bottleneck of three lines, the scorecard allowed identify and quantify the losses directly associated with the operation of the resource, as well as waste which have an impact on the production system. It was shown that the OEE is a tool for the promotion of continuous improvement, in that it enabled the prioritization and the development of actions aimed at reducing the main waste identified. It was found that even minor losses influence on an equipment should be assessed, as they may represent opportunities for improvement of simple and rapid deployment or with impact in several work centers.
In the implementation phase of the bookmark, the critical factors identified were training, the clear definition of the losses to be pointed and the monitoring of initial records with the officials responsible for data collection. When using the indicator, it was observed that the participation of operators in discussions of results stimulated their involvement with the tool and with the proposition of improvements.
Manual data collection proved to be cumbersome, due to the need of entering a large number of records in Excel spreadsheets. A large part of these records was already entered in the computerized system. For this reason, it was proposed an evaluation of the system in order to check if this could be used to calculate the indexes and index finger.
For the study, equipment availability was the largest factor impacting the OEE and the times of exchange for lots/products the major causes of interruption of operation of the feature. Through the rapid exchange of tools, the time of set up of the equipment were reduced by approximately 70%. Depending on the equipment being the resource bottleneck of production lines of three medicines to the institution, the reduction of the time of preparation of the machine increased global flow capacity of these lines. With the improving of equipment performance, this will no longer be a resource bottleneck, and the application of OEE may be extended to other critical machines and lines for the institution.
High impact machine Exchange times various production processes, as well as the occurrence of random crashes and the processing time higher than the theoretical, among other identified through the OEE. The indicator promotes the continuous improvement of the performance of equipment and, ultimately, of the manufacturing operations. Using the OEE has generated a number of other improvements, some of which were adopted immediately and others will have their assessed in future deployments.
Ahuja, I. P. S. et Khamba, J. S. (2008), “Total productive maintenance: literature review and directions”, International Journal of Quality & Reliability Management, Vol. 25 No. 7, pp. 709-756.
Alvarez, R. R. et Antunes Junior, J. A. V. (2001), “Takt-time: conceitos e contextualização dentro do sistema toyota de produção”, Gestão & Produção, Vol. 8 No. 1, pp. 1-18.
Badiger, A. S. et Gandhinathan, R. (2008), “A proposal: evaluation of OEE and impact of six big losses on equipment earning capacity”, International Journal of Process Management and Benchmarking, Vol. 2 No. 3, pp. 234-248.
Basu, P., Joglekar, G., Rai, S., Suresh, P. e Vernon, J. (2008), “Analysis of Manufacturing Costs in Pharmaceutical Companies”, Journal of Pharmaceutical Innovation, Vol. 3, No. 1, pp. 30-40.
Brasil. Lei nº 8.666, de 21 de junho de 1993. Regulamenta o artigo 37, inciso XXI da Constituição Federal, institui normas para licitações e contratos da Administração Pública e dá outras providências. Brasília, Diário Oficial União, 22 Junho de 1993.
Friedli, T. et Goetzfried, M. (2010), “In retrospect: A summary of operational excellence in the pharmaceutical industry in 2006”, em Friedli, T. et al. (Org.), The pathway to operational excellence in the pharmaceutical industry, Editio Cantor Verlag, Aulendorf, pp. 18-41.
Gilmore, M. et Smith, D. J. (1996), “Set-up reduction in pharmaceutical manufacturing: an action research study”, International Journal of Operations & Production Management, Vol. 16 No. 3, pp. 4-17.
Glatt Pharmaceutical Services, “Pan Coating”, disponível em: http://www.glatt.com/cm/en/equipment/coating.html (Acesso em 18 de Janeiro de 2012).
Hansen, R. C. (2006), Eficiência global dos equipamentos uma poderosa ferramenta de produção/manutenção para o aumento dos lucros, 1 ed., Bookman Companhia, Porto Alegre, RS.
Hasenclever, L., Fialho, B. C., Oliveira, M. A., Oliveira, E. A., Silva, H. F. e Bermudez, J. A. Z. (2008), “Diagnóstico e papel dos laboratórios públicos na capacitação tecnológica e atividades de P&D da indústria farmacêutica brasileira”, em Buss, P. M. et al. (Org.), Medicamentos no Brasil: Inovação e acesso, Fiocruz, Rio de Janeiro, pp. 199-235.
Herlant, M. (2010), “Restoring the balance: a strategic role for operations”, em Friedli, T. et al. (Org.), The pathway to operational excellence in the pharmaceutical industry, Editio Cantor Verlag, Aulendorf, pp. 64-77.
Junker, B. H. (2009), “Application of Overall Equipment Effectiveness to Biopharmaceutical Manufacturing”, BioPharm International, Vol. 22, No. 5, pp. 40-50.
Muchiri, P. et Pintelon, L. (2008), “Performance measurement using overall equipment effectiveness (OEE): literature review and practical application discussion”, International Journal of Production Research, Vol. 46, No. 13, pp. 3517–3535.
Pinto, E. J et Fernandes, I. A. (2001), Teoria e Prática na Indústria Farmacêutica, 1 ed., Fundação Calouste Gulbenkian, Lisboa.
Prates, C. C. et Bandeira, D. L. (2011), “Aumento de eficiência por meio do mapeamento do fluxo de produção e aplicação do índice de rendimento operacional global no processo produtivo de uma empresa de componentes eletrônicos”, Gestão & Produção, Vol. 18, No. 4, pp. 705-718.
Santos, M. C. B. G. et Pinho, M. (2012), “Estratégias tecnológicas em transformação: um estudo da indústria farmacêutica brasileira”, Gestão & Produção, No. 19, pp. 405-418.
Sugai, M., Mcintosh, R. I. e Novaski, O. (2007), “Metodologia de Shigeo Shingo (SMED): análise crítica e estudo de caso”, Gestão & Produção, Vol. 14, No. 2, pp. 323-335.
Sujkowski, A. (2006), “Além do OEE”, Pharmaceutical Technology do Brasil, Vol. 12, No. 3, pp. 90-94.
Vargas, M. A., Gadelha, C. A. G., Maldonado, J. M. S. e Barbosa, P. R. (2009), “Reestruturação na indústria farmacêutica mundial e seus impactos na dinâmica produtiva e inovativa do setor farmacêutico brasileiro”, disponivel em: http://www.sep.org.br/artigos/download?id=1620 (Acesso em 30 de Outubro de 2013).