1.1. State of the Art
TPM (Total Productive Maintenance), the most adopted management philosophy for maintenance activities, is an alternative method that integrates maintenance concepts and quality through daily inspection performed by trained operators. Its implementation aims to eliminate the significant stoppage causes, changeovers, and breaks in production [
1,
2]. One of TPM’s fundamentals is focused maintenance—that is, systematic identification and mitigation of losses [
3]. SMED is a mitigation loss analysis method that reduces downtime and is commonly applied to machines’ setups [
4]. Lack of quality accounts for a significant amount of production losses [
5]; as such, the machines’ performance must be guaranteed, thereby avoiding problems related with lack of quality. With regard to the tire industry in particular, more companies are adopting preventive and predictive calibration to avoid machine precision errors. The frequency of calibration is a commitment to balancing production pace with the need to maintain quality levels [
6].
SMED is a methodology first introduced by Shingo [
7] in 1985 to tackle the increasing necessity of setups due to small batch sizes and high variation in production. A setup refers to a set of activities to prepare a machine for manufacturing a product. Even though the methodology is old, recent research shows a higher volume of publications in recent years, showing that SMED is still used as a management tool for process improvement [
8]. Silva et al. [
4] concluded that SMED should be implemented with other lean tools such as 5S, standard work, kaizen, Overall Equipment Efficiency (OEE), total productive maintenance, poka-yoke, Value Stream Mapping (VSM), A3 methodology, and visual management in order to be effective. Moreover, the study recommended the involvement of senior management for team motivation and monitoring results for consolidation of gains. Monteiro et al. [
9] conducted a study of a metalworking company that supported these claims, concluding that using just one lean tool is ineffective. They used the tool VSM to correctly identify problems, and the implementation of SMED allowed a 40% reduction in setup time [
9]. Sousa et al. [
10] conducted a study in the cork industry, in which they used SMED combined with VSM and an A3 model to monitor the project’s development, which led to a 43% reduction in changeover time. The DMAIC cycle was successfully applied in a recent study [
11], leading to an increase in production. One of the management tools used was SMED—specifically in the improvement phase, to reduce the changeover time. This application led to a production increase of 44% in the manufacturing of wood products. One way to know whether the SMED can help is to analyse key performance indicators such as OEE and specifically availability.
Pinto et al. [
12] implemented Key Performance Indicators (KPIs) in the production of parts for the automotive industry to control overall manufacturing performance, leading to the use of lean management tools. The SMED methodology was used to reduce setup time by 11% with the help of the 5S tool. An OEE of 90% was achieved, mainly due to improvements in availability. In another study [
13], the application of SMED in a production process of interconnection axles increased OEE by 8%. SMED can be used for other goals as well. For example, Brito et al. [
14] used it to reduce setup time and ergonomic conditions. A 46% reduction in setup time was achieved while improving ergonomic conditions. Another study focused on the application of the muscle fatigue assessment method and the Taguchi method integrated with conventional SMED [
15]. The study was performed in an aluminium profile manufacturing factory, achieving a 62.5% improvement (regarding setup times), showing that integrating ergonomic risk analysis can lead to a further reduction in setup times.
Recently, a study proposed a new method called SWAN, which is the full integration between five whys analysis and SMED [
16]. It consists of a practical analysis tool whose goal is to determine the problems and their causes with regard to setup and develop suitable countermeasures. Indeed, the application of this method was very successful, with a 75% reduction in the setup time of a screen-printing machine. Ahmad et al. [
17] implemented five whys and SMED with positive results, reporting a 44% reduction in changeover time. The authors introduced cause-and-effect analysis at the beginning of the study, along with Ishikawa-diagram-based analysis and a conceptual decision model, which consisted of analysing each task to evaluate the chance of eliminating, converting, combining, or simplifying those tasks. When it comes to improving availability in a machine or production line, setups can represent a significant part of the total time wasted, as along with maintenance activities. Even though maintenance activities are performed to reduce downtime due to breakdowns and failures, their execution time can be reduced and optimised. For example, a study in the automotive industry implemented autonomous maintenance with the objective of improving machines’ availability [
18]. The autonomous maintenance was related to cleaning operations, organisation, and daily checks that resulted in a 10% increase in availability, a reduced breakdown rate, and a decrease in MTTR (Mean Time to Repair) due to the use of visual management and assessment operations. Ribeiro et al. [
19] used lean maintenance tools for problem identification, and an action plan was implemented to find the root causes of the main problems. The tools used were 5S, visual management, and a training program for the workers. The implementation resulted in an increase in the availability and improvement of other Key Performance Indicators.
1.2. Applying SMED to Preventive Maintenance Tasks
Borris et al. [
20] suggested that it is possible to apply the SMED methodology to preventive maintenance tasks. They also suggested the use of RCM (Reliability-Centred Maintenance) to handle the schedule and ensure the correct execution with the use of 5S.
The main goal is to minimise the machines’ downtime; usually, this refers to a setup, but it could also be applied to other procedures. There are two main principles regarding Borris’s [
20] suggestion:
By deciding between external and internal activities, it is possible to identify which tasks make it impossible to run the machine and which tasks can be performed during production.
By reviewing each action at a practical level, it is possible to identify which tasks are essential, need to be improved, or can be removed.
As seen from the aforementioned studies, SMED is a mitigation loss analysis method that, when employed correctly, can result in significant improvements with regard to reducing the time taken by various setup tasks. Indeed, SMED is mainly applied to the setup of various manufacturing processes [
21]. Setup is quite an important step in production processes; however, as previously mentioned [
6], maintenance and calibration procedures are also very important to the manufacturing process. These procedures guarantee the machines’ production quality, effectively reducing machine downtime due to breakdowns, and even cutting productivity losses due to the presence of defects in produced parts; this can be somewhat related to Zero-Defect Manufacturing, where the quality of the production is constantly evaluated, trying to extract useful information to improve process productivity [
22]. Maintenance and calibration procedures can be quite time-consuming, and there are no specific tools to analyse and optimise these types of procedures in current research. With the capabilities of SMED, there is an opportunity to apply this management tool to these types of procedures, as they are complex and entail a lot of different tasks. As such, in the present study, the use of SMED methodology applied to a calibration procedure of a tire manufacturing machine is proposed. It was observed that the Machine Tolerance Check (MTC) procedure represents a significant impact on the machine’s downtime. This procedure was evaluated and SMED was implemented, effectively optimising the total amount of time required to perform the calibration procedure. The knowledge acquired through the realisation of this work could be useful for other researchers and people involved in the tire industry or similar industries to improve processes and procedures, reducing the downtime and increasing the overall equipment efficiency. Thus, this work does not present a new theory but, rather, extends the use of a well-known methodology in a different application, opening new horizons for people looking for improving their processes.