Samir.
Evaluation of Supplier Performance Effectiveness Measurement using the SCOR (Supply Chain Operations Referenc.
and ANP (Analytic Network Proces.
Method Approach Evaluation of Supplier Performance Effectiveness Measurement using the SCOR (Supply Chain Operations Referenc.
and ANP (Analytic Network Proces.
Method Approach (Case Study: Supply of Silica Powder to PT.
Freeport Indonesia - Java Integrated and Industrial Port Estate (JIIPE).
Gresi.
Samsir 1.
I Ketut Gunarta 2 Department of Industrial and System Engineering Institut Teknologi Sepuluh Nopember Surabaya.
Email: 1samsir7@gmail.
com, 2gunarta@ie.
Received: 2024-08-05 Received in revised from 2024-08-05 Accepted: 2024-09-30 Abstract Companies must be able to provide quality products at relatively efficient prices and distribute them quickly to survive and excel in competition.
Companies need to collaborate with various parties to innovate and create competitive advantages.
Suppliers are essential actors as providers of resources that companies need precisely, quickly, and efficiently, so good supply chain management is required.
Companies must be able to assess supplier performance appropriately because this is the key to the success of successful SCM.
The object of this research was carried out at the company PT.
Freeport Indonesia.
This company experienced several problems related to the instability of the supply of silica powder as a reducing agent for copper ore, such as non-fulfilment of order quantities, delays, price changes and so on.
This research aims to identify appropriate criteria related to supplier performance using the SCOR (Supply Chain Operations Referenc.
and ANP methods in the companies From the results of this research, the best supplier criteria will be obtained based on quantitatively weighted classifications.
Keywords: Analytic.
Network.
Performance.
Relationship.
Supplier Introduction Indonesia is only able to produce 276,200 metric tons of copper smelting products.
Indonesia is a country that makes a lot of copper minerals compared to other countries.
However.
Indonesia is still in a lower position for the smelting process compared to other countries .
Indonesia is ranked below China, the United States and India.
India defeated Indonesia.
Even though this country does not produce much copper mineral production, it can make more smelting products than Indonesia, so this needs to be improved by the Indonesian government .
On January 12 2014.
President Susilo Bambang Yudhoyono stipulated the enactment of Government Regulation Number 1 of 2014 concerning prohibiting raw mining exports as a form of realization of Law No.
4 of 2009 concerning Mineral and Coal Mining.
Thus, mining companies must establish mineral processing plants known as smelters to support this goal .
One of Indonesia's largest copper mining sites is in Irian Jaya, which PT manages.
Freeport Indonesia and one of the copper ore processing sites is in the Gresik area under the company PT Indonesian Smelting.
The location in Gresik was chosen for several reasons, including ease of transportation related to cost savings.
Gresik is an industrial area with various facilities that can reduce waste from copper ore refineries .
PT.
Smelting Indonesia in processing copper ore certainly requires suppliers ranging from raw materials, machines and equipment, additional materials, etc.
Still, the research discussed is related to the supply of silica as the primary material put into the furnace to lower the boiling point of the liquid:
copper and gold.
Mitigating supply chain risks and evaluating supplier selection is vital in the continuity of production at PT.
Freeport Indonesia.
Suppose a risk in the supply chain occurs, such as late delivery of raw materials.
In that case, the business sector will also be disrupted, which will affect the company 68 Journal of Applied Sciences.
Management and Engineering Technology.
Vol 5.
No 2, 2024: 67Ae77 in fulfilling customer requests, and the company may experience losses.
PT Indonesian Smelting as a company operating in the copper ore refining smelter sector.
Freeport Indonesia must compete with similar companies.
Problems that occur at PT.
Freeport Indonesia is a mismatch in supplier performance as a partner that has been targeted with its realization.
This discrepancy is related to order fulfilment that could be more optimal in terms of quality and quantity due to the lack of implementation of structured risk management to identify and mitigate risks that occur, especially in the supply chain function, one of which is delays in order delivery .
Therefore, selecting a supplier that is less than optimal will cause delays in the required raw materials, so the project schedule that was initially planned will be delayed .
A measurement is needed to determine the performance of a company's supply chain using the Supply Chain Operations Reference (SCOR) method .
SCOR generally provides a business process framework, work indicators, and supporting collaboration between partners to increase management effectiveness and improve the company's supply chain .
To overcome existing problems, researchers only focus on existing issues using SCOR 11.
0, where creating a performance measurement system based on SCM aims to control and evaluate performance continuously to create a competitive advantage .
Risk management and optimal supplier selection are the right solutions to prevent copper ore refining project delays .
Identifying risks that occur or have the potential to happen in the supply chain and the selection of appropriate criteria, sub-criteria, and alternative suppliers for selecting suppliers will significantly influence the continuity of production so that it can run optimally .
Based on the conditions described, this research was conducted to learn more about how supply chain risks are managed and supplier selection, especially in the copper ore refining project currently being carried out by PT Indonesian Smelting.
Method 1 Research Methods The data collection and processing process begins with explaining the stages of data collection, namely collecting secondary data in the form of performance indicators for supply chain relationship management in the industry and strengthening the methodology.
Meanwhile, at the primary data collection stage, data is collected through interviews and distributing questionnaires regarding key performance indicators for supply chain relationship management in the manufacturing industry, which will be tested on respondents.
Secondary data collection produces several general performance criteria for supply chain relationships in various sectors.
After adjustments were made to the research area, the manufacturing industry in the mining products sector, the supply chain relationship performance indicators tested were fewer.
In its implementation, additional recommendation indicators were obtained from interviews with respondents and experts .
xpert judgmen.
2 Problem Identification In the form of identifying problems that occur in general, to get a relevant problem to be addressed object of research.
This step is carried out by looking for relevant issues in the industry that require further study, both classic and actual problems.
Ultimately, this research took the trouble of evaluating the performance of the silica powder supply chain between PT.
Freeport Indonesia and its suppliers are the issues that will be discussed.
3 Literature review Problems found in the object of observation can be reviewed in two ways: literature review using literature studies and field studies.
Data Collection In the form of searching for data that will be used as input for data processing.
The types of data used in this research are primary and secondary data, where primary data is obtained through direct field observations, interviews and requests to complete questionnaires with related and competent parties such as logistics manager, operational manager, purchasing manager, procurement and so on.
Samir.
Evaluation of Supplier Performance Effectiveness Measurement using the SCOR (Supply Chain Operations Referenc.
and ANP (Analytic Network Proces.
Method Approach Meanwhile, secondary data is in the form of pre-existing data as a preference and usually takes the form of documentation such as data on machine components, time of failure, component prices, processing time per unit, machine operator costs and operator costs for repairs from PT Freeport Indonesia in the period September 2023 Ae November 2023.
Figure 1.
Flowchart of Research Methodologywd Data processing The initial step in data processing is for the researcher to carry out an analysis of each supplier.
Then, the suppliers are grouped using clustering analysis.
The dominant variables that describe the group are also identified.
From the results of data processing and supplier grouping, the SCOR concept identifies the development of assessment criteria for each supplier group.
At this stage, researchers carry out three types of data processing and calculations with several aspects of data processing and measurement, the first of which is supplier selection, among other selection criteria, standard selection procedures, feedback system, the effectiveness of negotiations and manufacturing standard contracts.
Meanwhile, the second stage of data processing is related to the application of technology and information about SCM, which includes types of information systems, effectiveness of information systems and improvements to supply chain information systems.
Meanwhile, the third stage of data processing is measurement related to supplier performance, which includes timeliness, quality accuracy, price accuracy, quantity accuracy, location accuracy, variety accuracy, service accuracy and SCOR criteria consisting of Plan.
Source.
Make.
Deliver and Return.
70 Journal of Applied Sciences.
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No 2, 2024: 67Ae77 6 Research Analysis Techniques This research uses model construction from the ANP method.
The research model construction process consists of determining criteria, sub-criteria, and alternatives and formulating performance The analysis technique used in data processing in this research is the ANP method.
After collecting data from respondents, data in the form of assessments between criteria must be processed for analysis.
Data processing from the assessment results uses software that can accommodate decisionmaking models, including ANP.
In this research, the software used is Super Decision.
Results and Discussion 1 Selection of Performance Indicators The selection of performance indicators was produced after conducting interviews and giving questionnaires to several key informants to plan performance indicators that were previously unknown to the company.
Meanwhile, the questionnaire is used to select performance indicators to determine which indicators still need to be known about the company's performance.
In Table 1, it is explained that there are 22 performance indicators and 16 performance indicators selected by the company.
The following are 16 indicators chosen by the company, and their formulation includes:
Table 1 Performance Indicators Process Performance Indicators Forecast accuracy PLAN (Planning Proces.
SOURCE (Procurement Proces.
MAKE (Production Proces.
DELIVER (Delivery Proces.
RETURN (Return from Custome.
Raw materials Plan accuracy Planning cycle time Percentage suppliers with EMS Timely Delivery by Supplier Delivery Item Accuracy for Supplier Inventory Accuracy Raw Materials Adherence to the Production Schedule Product Defect from Production Formulation 100 -( 100 -( Permintaan aktual Kebutuhan aktualOePeramalan kebutuhan kebutuhan aktual Planning time x 100% Total pemasok Jumlah frekuensi pengiriman tepat waktu 100 -( 100 -( x 100% Total frekuensi pengiriman Jumlah unit dipesanOeJumlah unit diterima x 100% x 100% Total Line Jumlah produk cacat Number of cases of machine failure 100 -( Scrap Total produksi Jumlah frekuensi pengiriman tepat item Total frekuensi pengiriman 100 -( x 100% Jumlah unit dikirim Oe Jumlah unit diterima Jumlah unit dikirim 100 -( Jumlah unit di gudang Fulfilment line schedule Day Jumlah unit dipesan Jumlah unit di gudang Oe Jumlah unit tercatat Number of Trouble Machines Material Efficiency (Yiel.
Percentage of Solid Waste Recycling Jumlah pemasok yang memiliki EMS Total produksi Delivery Item Accuracy by The Company Delivery Quantity Accuracy by The Company Order Delivered Faultless by The Company Return rate from customers Unit Permintaan aktualOePeramalan permintaan Jumlah unit cacat Jumlah unit dikirim Jumlah produk dikembalikan x 100% Total produk dikirim Jumlah limbah padat yang dapat didaur ulang Total limbah padat 2 Validation of Performance Indicators PLAN (Planning Proces.
Forecast Accuracy Forecast accuracy is the accuracy of forecasting sales demand.
x 100% Case Samir.
Evaluation of Supplier Performance Effectiveness Measurement using the SCOR (Supply Chain Operations Referenc.
and ANP (Analytic Network Proces.
Method Approach
Table 2 Forecast Accuracy June 2023
Demand
Forecasting 1,275 tons July 2023
August 2023
September 2023
October 2023
November 2023
1150 tons 925 tons 560 tons 675 tons 800 tons Month
Actual
Demand
1,177
1008 tons 750 tons 640 tons 785 tons 878 tons Difference Results -98 tons -142 tons -175 tons 80 tons 110 tons 78 tons As a result of the calculation above, the forecast accuracy value in June 2023 is 103.
with the company forecasting demand for silica raw materials for the refinery process in that month at 1275 tonnes and actual demand for refinery process requirements at 1177 tonnes, so at In June 2023 there is an excess supply of silica of 98 tons for the Aurum refinery process, and this is by the natural conditions that the price of gold on the world market in June.
July and August 2023 is still relatively high so that the Aurum production and refinery process is also starting to fall.
However, in September.
October and November of 2023, when gold prices begin to stabilize and world demand for gold increases, demand for silica as the primary material for the refinery process increases, and suppliers cannot meet the need for silica raw materials according to PT Indonesian Smelters.
Raw Material Planning Accuracy Raw Material Planning Accuracy is the accuracy percentage in predicting the need for silica raw materials.
Table 3 Raw Material Planning Accuracy Month June 2023 July 2023 August 2023 September 2023 October 2023 November 2023 Forecasting the Need for Main Raw Materials 200 ton 000 ton 750 ton 000 ton 200 ton 500 ton Actual Main Raw Material Needs 700 ton 750 ton 850 ton 325 ton 780 ton 375 ton Difference Results 500 ton 750 ton 100 ton 325 ton 580 ton 875 ton As a result of the calculation above, the raw material planning accuracy value in June 2023 is 90.
The company predicted the need for the main raw material, silica, to be 14,200 tons and the actual need for silica to be 15,700 tons, so in June, there is a difference of 1500 tons.
SOURCE (Proses Pengadaa.
Percentage Supplier with Environmental Management System The percentage of suppliers with an environmental management system is the percentage of supplier selection that has an environmental management system.
Table 5.
List of PT.
Partner Suppliers.
Indonesian Smelters No.
Supplier Name PT.
Delta Puro Indonesia PT Alter Abadi Tbk PT.
Jara Silika PT.
Sibara Bestari PT.
Tochu Silica
OPAL
EMAS
IPU
PROPER
EMS
En En En En En All suppliers from PT.
Indonesian Smelters have various requirements related to environmental management systems, including IPAL (Waste Water Treatment Plan.
B3 Processing (Processing of Hazardous and Toxic Material.
EMAS (Echo Management and 72 Journal of Applied Sciences.
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Vol 5.
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IPU (Air Pollution Control Installatio.
PROPER and EMS (Environment Management Syste.
Timely Delivery Performance by Supplier Timely delivery performance by suppliers is when suppliers send raw materials according to the specified time.
Table 6.
Timely Delivery Performance by Supplier Raw Material Delivery Four times Four times Four times Two times Three times Three times Month June 2023 July 2023 August 2023 September 2023 October 2023 November 2023 Timely Delivery of Raw Materials Four times Four times Two times One time Two times One time Difference Percentage 0 times 0 times Two times One time One time Two times The calculation above's results can be explained by the fact that in November 2020, raw materials were delivered four times, and there were no delays, so the performance value was 100%, the same as in December 2020 and January 2021.
However, in February-April 2021, there were delays in the delivery process.
Delivery Item Accuracy by Supplier Delivery Item Accuracy by Supplier is the performance of accurate delivery of raw materials for the correct items by the supplier within the specified time.
Table 8.
Delivery Item Accuracy by Supplier Month Raw Material Delivery June 2023 July 2023 August 2023 September 2023 October 2023 November 2023 Four times Four times Four times Two times Three times Three times Delivery of Raw Materials on the Right Items Four times Four times Four times Two times Three times Three times Difference Percentage 0 times 0 times 0 times 0 times 0 times 0 times The results of the calculations above show that in June 2023 - November 2023, the value of delivery item accuracy by the supplier was 100%, which shows that during these 6 months, the supplier sent the right raw material items according to the silica raw materials ordered by the Delivery Quantity Accuracy by Supplier Delivery quantity accuracy by the supplier is a percentage of supplier accuracy in the quantity of silica raw materials sent.
This data is contained in Table 4.
7 as follows:
Table 9.
Delivery Quantity Accuracy by Supplier Month June 2023 July 2023 August 2023 September 2023 October 2023 November 2023 Raw Materials Ordered 200 ton 000 ton 750 ton 000 ton 000 ton 500 ton Raw Materials Accepted 200 ton 000 ton 750 ton 000 ton 200 ton 500 ton Difference Percentage 0 kg 0 kg 0 kg 0 kg 0 kg 0 kg MAKE (Production Proces.
Adherence to the Production Schedule Adherence to the production schedule is the accuracy of the production process schedule by production planning.
Samir.
Evaluation of Supplier Performance Effectiveness Measurement using the SCOR (Supply Chain Operations Referenc.
and ANP (Analytic Network Proces.
Method Approach Table 11.
Adherence to the Production Schedule Month June 2023 July 2023 August 2023 September October 2023 November 25 times 27 times On-Time Production 20 times 21 times 24 times 17 times 13 times Nine times Four times 19 times 14 times 23 times 20 times Five times Three Production Difference Percentage Five times Six times Seven Product Defect From Production Product defects from production are defective products resulting from the production Table 12.
Product Defect From Production Month June 2023 July 2023 August 2023 September 2023 October 2023 November 2023 Production 275 ton 150 ton 925 ton 560 ton 675 ton 800 ton Inappropriate Results 1,5 ton 1 ton 1 ton 0 ton 5 ton 1 ton Percentage 0,11 % 0,08 % 0,1 % 0,07 % 0,12 % The result of the calculation above is that in June 2023, the value of product defects from production was 0.
11% because that month in the production process, products from the refinery were still impure or dirty, the same as in July 2023.
August 2023.
October, and November 2023.
DELIVER (Delivery Proces.
Delivery Item Accuracy by The Company The company's delivery item accuracy is the percentage of accuracy of delivery items for refinery products produced by PT Smelting Indonesia in accordance with PT Freeport Indonesia's requests.
Table 13.
Delivery Item Accuracy by The Company Month June 2023 July 2023 August 2023 September 2023 October 2023 November 2023 Product Delivery 20 times 24 times 19 times Ten times 13 times 23 times Delivery of the Right Product Item 20 times 24 times 19 times Ten times 13 times 23 times Percentage In June 2023 PT.
Smelting Indonesia sent refined products 20 times and precisely delivered the refined product items according to PT's request.
Freeport Indonesia 20 times, this shows that PT.
Smelting Indonesia sends products to PT.
Freeport Indonesia, according to the product items that have been ordered.
RETURN (Customer Return Proces.
Return Rate From Customer The return rate from customers is the percentage of return for PT refinery craft products.
Freeport Indonesia to PT.
Indonesian Smelting.
74 Journal of Applied Sciences.
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No 2, 2024: 67Ae77 Table 14.
Return Rate from Customer Month June 2023 July 2023 August 2023 September 2023 October 2023 November 2023 Number of Products shipped 168 ton 008 ton 750 ton 640 ton 785 ton 883 ton Number of Products Returned 0 ton 0 ton 0 ton 0 ton 0 ton 0 ton Percentage Table 14 explains that in June 2023.
PT.
Smelting Indonesia sent 1168 tons of refined products, with the total quantity of refined products returned by PT.
Freeport Indonesia as much as 0 tons.
This shows that no refinery products were sent to PT.
Freeport Indonesia is out of specification.
3 Selection of Criteria and Sub-Criteria using the ANP Method Determination of Criteria and Sub-criteria The criteria and sub-criteria considered in selecting a vendor/supplier are determined by discussions with PT Smelting Indonesia and PT Freeport Indonesia through an open questionnaire.
Table 15.
Determination of Criteria and Sub-Criteria No.
Determination of Criteria and Sub-Criteria before FGD Criteria Index Sub Criteria P1.
Demand forecasting P2.
Goods procurement plan
PLANS
Scheduling of sorting, processing and P3.
finishing processes Carrying out goods procurement S1.
S1.
Goods receipt
SOURCE
S1.
Storage of goods from suppliers S1.
Storage of sorted products S2.
Storage of finishing products M1.
Sorting product M1.
Processingproduct
MAKES
M1.
Quality control assessment M2.
Finishing D2.
Goods sales transactions D2.
Ensure legality and permits.
DELIVER
D2.
Delivery of goods D2.
Ensure products are received as agreed.
Accept returns when goods do not R1.
match the agreement Returning goods to suppliers when they R1.
do not meet specifications R1.
Serve potential customers optimally.
RETURN
Providing R2.
treatment to customers Provide R2.
R2.
Provide Determination of Criteria and Sub-Criteria after FGD Criteria Index Sub Criteria P1.
Forecast accuracy P2.
Raw materials Plan accuracy PLANS Planning cycle time P3.
S1.
SOURCE
MAKES
DELIVERY
Percentage suppliers with EMS S1.
S1.
Timely Delivery by Supplier Delivery Item Accuracy for Supplier S1.
Inventory Accuracy of Raw Materials M1.
M1.
M1.
M2.
D2.
D2.
Adherence to the Production Schedule Product Defect from Production Number of Trouble Machines Material Efficiency (Yiel.
Delivery Item Accuracy by The Company Delivery Quantity Accuracy by The Company D2.
Order Delivered Faultless by The Company R1.
Return rate from customers R1.
Percentage of Solid Waste Recycling RETURN Relationship between Organizational Strategy and Business Process Mapping Results Based on SCOR Model In order to obtain key indicators that effectively represent the company's performance, it requires not only a description of the business process but also aspects related to what the company wants to achieve, as well as the company's focus and positioning in competing in the market, which can be reflected in the organization's strategy.
Samir.
Evaluation of Supplier Performance Effectiveness Measurement using the SCOR (Supply Chain Operations Referenc.
and ANP (Analytic Network Proces.
Method Approach Ranking Criteria Table 16.
Local Criteria Weighted Ranking Criteria
DELIVERY
SOURCE
MAKE
RETURN
PLANS
Local Weight Ranking The local weight of the DELIVERY (D) criterion is in first place with a value of 0.
1738472 or 38%, which means that this criterion is considered the most important in selecting criteria.
It is followed by the SOURCE (S) criterion of 0.
1693613 or 16.
MAKE (M) of 0.
1069284 or 69%.
RETURN (R) of 0.
0988179 or 9.
88%, and in last place PLAN (P) of 0.
0857299 or 8.
Organizational Strategy Business Process Mapping No.
Strategy No.
Providing products with quality above the market average in general Ensure products are available when customers request them according to the requested product quality level Provide quality assurance by the agreement until the customer receives the product.
Index Process P1.
P2.
P3.
S1.
S1.
S1.
S1.
R1.
Forecast accuracy Raw materials Plan accuracy Planning cycle time Percentage suppliers with EMS Timely Delivery by Supplier Delivery Item Accuracy for Supplier Inventory Accuracy of Raw Materials Adherence to the Production Schedule Product Defect from Production Number of Trouble Machines Material Efficiency (Yiel.
Delivery Item Accuracy by The Company Delivery Quantity Accuracy by The Company Order Delivered Faultless by The Company Return rate from customers R1.
Percentage of Solid Waste Recycling M1.
Providing qualified before-sales service facilities to prospective customers as well as maximum after-sales service based on the customer's priority level towards the Providing exclusive treatment to business partners intensively to improve the performance of business partners towards the company M1.
M1.
M2.
D2.
D2.
D2.
SCORE
MODEL
PLANS
SOURCE
MAKES
DELIVERY
RETURN
Figure 2.
Relationship between Organizational Strategy and SCOR Model Business Process Mapping Results Sub Criteria Ranking Table 4.
33 Global Weight Ranking of Sub-Criteria Criteria Delivery Item Accuracy for Supplier(S1.
Product Defect from Production(M1.
Material Efficiency (Yiel.
(M2.
Order Delivered Faultless by The Company(D3.
Forecast accuracy(P1.
Planning cycle time(P3.
Return rate from customers(R1.
Percentage suppliers with EMS(S1.
Raw materials Plan accuracy(P2.
Delivery Quantity Accuracy The Company(D2.
Number of Trouble Machines(M1.
Adherence to Production Schedule(M1.
Inventory Accuracy of Raw Materials(S1.
Delivery Item Accuracy by The Company(D1.
Local Weight Ranking 76 Journal of Applied Sciences.
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Percentage of Solid Waste Recycling(R1.
The data processing results show that the highest priority criterion is DELIVERY (D) while the sub-criteria is Delivery Item Accuracy for Supplier (S1.
as the top one.
This indicates that there is a connection between criteria and sub-criteria that are in one cluster.
The criteria and sub-criteria here influence each other in determining the available choices.
Apart from that, in calculating priority criteria, the SOURCE (S) criterion is in the second highest position, while in sub-criteria calculations, the Product Defect from Production (M1.
and Material Efficiency (Yiel.
(M2.
sub-criteria get the highest scores.
Therefore, when selecting a supplier.
PT.
Smelting Indonesia needs to give priority attention to the DELIVERY (D) and SOURCE (S) criteria as well as the Delivery Item Accuracy for Supplier (S1.
and Product Defect from Production (M1.
and Material Efficiency (Yiel.
(M2.
Conclusion In general, using the SCOR method approach to assess supplier performance with these 16 indicators, the average is excellent, but several performance indicators still need to be improved, namely raw material planning accuracy is still 90.
4%, adherence to production schedule is still 80%, product defects from production 0.
11% and material efficiency .
Using the ANP approach, the criteria and sub-criteria here influence each other in determining the available choices.
The highest priority criteria calculation is DELIVERY (D), and the SOURCE (S) criterion is in the second highest position, while in sub-criteria calculations, the sub-criteria Product Defect from Production (M1.
and Material Efficiency (Yiel.
(M2.
get the highest value.
Therefore, when selecting a supplier.
PT.
Smelting Indonesia needs to give priority attention to the DELIVERY (D) and SOURCE (S) criteria as well as the Delivery Item Accuracy for Supplier (S1.
and Product Defect from Production (M1.
and Material Efficiency (Yiel.
(M.
Reference