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Inventory wastes contributing to downtime in figure 4 are due to stock-outs. The identified recurring stock-outs are shown in table 5 and the corresponding Pareto chart is shown in figure 8. Figure 8: Pareto analysis for inventory (stock-outs) waste

Figure 4 Inventory wastes contributing to downtime in figure 4 are due to stock-outs. The identified recurring stock-outs are shown in table 5 and the corresponding Pareto chart is shown in figure 8. Figure 8: Pareto analysis for inventory (stock-outs) waste

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Figure 1: Margarine production process at a Company X in Timbhahwe [4] The company has 22.5 working hours per day and operates on a full calendar month. There are 5 production lines for margarine at DX industries. Therefore the available time for production is 3375 hours on average per month. Of the 3375hours available the bulk is consumed by downtime with actual production taking place in 875hours a month on average. The flow-line for margarine production at the case study company is shown in Fig. 1 [4].
Figure 1: Margarine production process at a Company X in Timbhahwe [4] The company has 22.5 working hours per day and operates on a full calendar month. There are 5 production lines for margarine at DX industries. Therefore the available time for production is 3375 hours on average per month. Of the 3375hours available the bulk is consumed by downtime with actual production taking place in 875hours a month on average. The flow-line for margarine production at the case study company is shown in Fig. 1 [4].
Figure 2: Pasteurisation Graph for water phase DX industries The vegetable oil used in the manufacture of margarine is modified to harden it. There are three ways to modify oils and these are hydrogenation, rearrangement or fractionation. The hardened oil is then blended with ingredients such as vitamins, colours, flavours and emulsifiers. At the same time a mixture of water, brine and powdered ingredients is created. These two ingredient mixtures are blended together at temperatures around 50 - 60°C while being slightly mixed. This mixture or emulsion needs to be pasteurised at temperatures around 70 to 86°C. Pasteurisation can be defined as the partial sterilization of food, at a temperature that destroys harmful micro-organisms, without major changes in the chemistry of the food [5]. Figure 2 shows the graph of pasteurisation at the case study company.
Figure 2: Pasteurisation Graph for water phase DX industries The vegetable oil used in the manufacture of margarine is modified to harden it. There are three ways to modify oils and these are hydrogenation, rearrangement or fractionation. The hardened oil is then blended with ingredients such as vitamins, colours, flavours and emulsifiers. At the same time a mixture of water, brine and powdered ingredients is created. These two ingredient mixtures are blended together at temperatures around 50 - 60°C while being slightly mixed. This mixture or emulsion needs to be pasteurised at temperatures around 70 to 86°C. Pasteurisation can be defined as the partial sterilization of food, at a temperature that destroys harmful micro-organisms, without major changes in the chemistry of the food [5]. Figure 2 shows the graph of pasteurisation at the case study company.
a I IBM developed a conceptual framework of how their products are designed and manufactured globally [11]. This can be adopted as assessment framework for companies that have adopted world class manufacturing.
a I IBM developed a conceptual framework of how their products are designed and manufactured globally [11]. This can be adopted as assessment framework for companies that have adopted world class manufacturing.
Table1:Key implications of lean manufacturing [17]
Table1:Key implications of lean manufacturing [17]
Table 2: Typical ratio of activities in a processing company [19] This is a clear indication that up to 60% non-value adding activities at any manufacturing company can potentially be reduced greatly.
Table 2: Typical ratio of activities in a processing company [19] This is a clear indication that up to 60% non-value adding activities at any manufacturing company can potentially be reduced greatly.
Figure 3: Nine wastes in lean manufacturing [15] PISULY J. ANTS WaostOs Lit tC dll Llaluldaelul iis [il | The first step is to recognise what does and does not create value from the customer’s perspective [16]. Any material, process or feature which is not required for creating value from the customer’s perspective is waste and should be eliminated. Table 1 shows the different approaches of lean manufacturing and traditional manufacturing [17].
Figure 3: Nine wastes in lean manufacturing [15] PISULY J. ANTS WaostOs Lit tC dll Llaluldaelul iis [il | The first step is to recognise what does and does not create value from the customer’s perspective [16]. Any material, process or feature which is not required for creating value from the customer’s perspective is waste and should be eliminated. Table 1 shows the different approaches of lean manufacturing and traditional manufacturing [17].
Table 3: Waste Categorisation at DX Industries Fig. 6 below shows a Pareto Analysis of the waste in production. It shows that waiting and inventory wastes contributed 80% of the total production down time.
Table 3: Waste Categorisation at DX Industries Fig. 6 below shows a Pareto Analysis of the waste in production. It shows that waiting and inventory wastes contributed 80% of the total production down time.
Figure 5: Production time-downtime ratio
Figure 5: Production time-downtime ratio
Figure 7: Pareto analysis for waiting time International Journal of Innovative Technology and Exploring Engineering (IJITEE ISSN: 2278-3075, Volume-2, Issue-1, December 2012
Figure 7: Pareto analysis for waiting time International Journal of Innovative Technology and Exploring Engineering (IJITEE ISSN: 2278-3075, Volume-2, Issue-1, December 2012
A Future State Radar Map was developed from suggested improvements from the initial assessment. The results are shown in Fig. 9 below. Figure 9: Current State Radar Chart (CSRC) and Future State Radar Chart (FSRC) comparison using a 29 point lean assessment tool
A Future State Radar Map was developed from suggested improvements from the initial assessment. The results are shown in Fig. 9 below. Figure 9: Current State Radar Chart (CSRC) and Future State Radar Chart (FSRC) comparison using a 29 point lean assessment tool
Figure10: Current state production time-downtime ratio Downtime was reduced by 30% and this means an increase in plant availability by 1012.5 hours. A comparison of the Current State and Future State Production — Downtime Ratios is shown in Fig. 10 and Fig.11.
Figure10: Current state production time-downtime ratio Downtime was reduced by 30% and this means an increase in plant availability by 1012.5 hours. A comparison of the Current State and Future State Production — Downtime Ratios is shown in Fig. 10 and Fig.11.
Figure 11: Future state production time-downtime ratio Plant availability was improved from 26% of the available time to 56% of the total available time by cleaning wastes as defined by lean manufacturing.
Figure 11: Future state production time-downtime ratio Plant availability was improved from 26% of the available time to 56% of the total available time by cleaning wastes as defined by lean manufacturing.
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