**4.5 Discussion**

*Operations Management - Emerging Trend in the Digital Era*

The graph in **Figure 7** summarises the duration of downtime when any or a combination of the plant or equipment in the production network breaks down. The target of 180 and 170 hours per month was adopted for 2017 and 2018, respectively. The analysis of the information in the operational database showed that the monthly average duration of downtime for 2017 was 250 hours per month, which represents 38.8% above target. This translates into 2.9 days' production lost per month and an average of 34.8 days per year, resulting in a revenue loss equivalent to 1 month per year. However, in September 2018, the monthly average was about 170 hours, which is the benchmark set for the year. If this trend continued, there would be marked improvements in the duration of downtime in the plants on the company's production network, ensuring increased machine reliability and

Plant reliability can be described as the probability that the plant(s) in the production network will be available for effective production in a manufacturing industry. Plant reliability is influenced by the number of breakdowns, the length of time before repairs are concluded and the duration of downtime. Machine reliability is usually expressed in percentages. Positive improvements in the MTTR (like JIT) translate in the reduced duration of downtime as well as a reduction in the number of breakdowns. The plant reliability performance of the AICC was benchmarked

As shown in **Figure 8**, the plant reliability benchmark of the AIHC (the blue horizontal line) for 2017 was 75%. In comparison, the AICC achieved a monthly average of 68% (second red vertical bar from origin of the graph in **Figure 8**) for the same period. This is an indication that the plants of the AICC performed below that of the sister company, the AIHC. Although, the AICC, in September 2018, attained a reliability of 75%, (the red vertical bar, to the right, next to 2018 yearly average), this is still below the new benchmark of 80% set by the AIHC for 2018. However, if there were consistent improvements in the MTTR in the last quarter of

*4.4.3 Total downtime*

*4.4.4 Plant reliability*

improvements in production output.

against the performance of a sister industry, the AIHC.

the year, it may be possible to meet the benchmark set by the AIHC.

\*Development of maintenance management, preventive and breakdown maintenance

\*Benchmarking and identification of areas requiring performance improvements

database

machine reliability

\*Periodic analysis of operational details in CMMS

\*Improvements on MTTR (or JIT) and effects on

\*Develop synergy with finance, purchasing and store departments to ensure timely resourcing of spare parts for maintenance operations

**Industry Current use of CMMS tool Potential harnessed**

\*Making maximum use of the maintenance management

\*The synergy being created can facilitate the activation of the automation module

\*Progressing towards the practice

of smart maintenance

module

**70**

**Table 5.**

*Summary of findings.*

Adcock Ingrams Critical Care (AICC)

The manufacturing company demonstrated a higher level of harnessing the potential inherent in a typical CMMS through the practice of comprehensive maintenance management, which includes planned, preventive, proactive and breakdown maintenance. The practice includes the analysis of the information in the operational database of the CMMS. These analyses enabled the maintenance unit to know the impact of the frequency of breakdowns, the length of time before repairs are completed and the effect of the duration of downtime of machines on the reliability and availability of machines in the production line. The analysis exposed the impact of the length of downtime on the productivity of the company. This could be described in the following understandable terms.

*The average duration of downtime for 2017 was 250 hours per month, which is considerably higher than the benchmark, representing a level of 38.8% above target. This translates into 2.9 days' production lost per month and an average of 34.8 days per year, resulting in a revenue loss equivalent to 1 month per year.*

This realisation challenged the maintenance unit to improve on the MTTR. Success in the MTTR or JIT [3] is the product of appropriate maintenance planning, positive work ethics and the professional attitude of the workforce. This includes effective coordination between the maintenance unit, purchasing department, finance department and stores, the inventory control of stock and the timely availability of spare parts. It is important to note that the industry will have value for money through the effective management of an adequate stock of spare parts rather than purchasing on demand, which is more expensive [36]. Spares that are available reduce repair time and reduce the incidence of the 'fire-fighting approach' when sourcing spare parts. This enables the maintenance unit to strive towards achieving best practice, which suggests that 85% of repairs should be executed through planned maintenance and 15% through breakdown repairs [37]. These efforts culminate in the benchmarking of plant reliability with their sister industry. It is worth noting that plant reliability facilitates production planning, sales and marketing projection, achieving customers' satisfaction and profitability [37, 38].

The detailed analysis of the information in the operational database of plants in the production network enables maintenance units to identify area(s) requiring critical attention around which performance improvement strategies should be developed [39]. It provides intelligent information relating current performance against predetermined goals to decision-makers at all levels [19, 21]. This exercise challenges maintenance units to practise the art of continuous data collection, analysis and the interpretation of information to facilitate the development of appropriate improvement strategies [15]. Furthermore, it supports compliance activities, proposals for changes or requests for additional resources as it illuminates the link between strategies, performance and expected outcomes. It also achieves the objectives of smart maintenance [4, 19, 20].
