Material requirements planning system considering batch size and minimum order quantity for items of suppliers

doi:10.21203/rs.3.rs-2963352/v1

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Material requirements planning system considering batch size and minimum order quantity for items of suppliers

https://doi.org/10.21203/rs.3.rs-2963352/v1

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Material requirements planning (MRP) is an intelligent information system and a decision maker that determines the type of raw materials, the amount of them, and their supplying time in order to realize production schedule of products and work-in-process items in a manufacturing system. The inputs of MRP model include bill of materials, master production schedule, lead times, and inventory of the items. The main output of the model is material supplying schedule, and MRP sub-outputs include purchase advice, control report for the consumed items, financial planning, budgeting, and so on.

If in each manufacturing system we split production costs into three kinds of raw material costs, salary costs, and overhead costs, in the real environment, 60-90 percent of total costs are related to raw material costs. Therefore, in each manufacturing system, it is necessary to consider an appropriate inventory control system to control the costs of inventory system and provide right inventory, with right amount, at the right time, at the right price, and with appropriate quality.

In this research, two constraints on the size of the packaging of goods and the minimum order amount that a supplier provides for a product are added to the model. By closing the existing gap, the mentioned model can be operationally implemented and provide appropriate decision-making outputs. Therefore, at first, we will review the introduction and previous researches that have been done in this field. Then, we will describe the components of the material requirements planning model. In the following, the above-mentioned two constraints are added to the model and the material requirements planning system is presented.

Physical sciences/Engineering/Mechanical engineering

Physical sciences/Mathematics and computing/Software

Material requirements planning

Inventory control system

Bill of materials

Master production schedule

Lead time

Supply chain

Supply chain is a network that includes three stages of purchasing raw materials from factories and suppliers, performing operations on raw materials and producing products, and distributing these products to customers. The components of these steps are shown in Figure 1. Supply chains are seen both in the industry and production sector and in the service sector, and the complexity of the chain can be different from each economic enterprise to another enterprise [1]. There are many tools available to manage supply and demand and maintain market balance to increase chain profits. For example, it is possible to influence the supply level by determining the optimal transportation and distribution system, changing the production capacity and determining different inventory levels, and by applying marketing and advertising principles, the demand level can be changed.

Among all available tools, the inventory control system plays an important role to increase the profitability of the supply chain, maintain and expand the customer network, and improve the organization. A proper inventory control system can respond appropriately to system demands and ultimately affect revenue. In fact, the implementation of a suitable inventory system is the main and key pillar for organizations that purchase raw materials, produce their product(s) and distribute for sale in the market.

Manufacturing companies can be divided into MTS[1] and MTO[2], or a combination of the two, depending on whether they have mass production or produce based on customer orders. To deal with the possible changes in the environment in any system, including MTS and MTO systems, an important factor such as flexibility plays a fundamental role, which can be created with solutions such as the arrangement of machines, specialized human resources, etc.

Organizations with an MTS system produce and store standard goods based on demand history and then respond to customer demand based on their inventory, such as Amazon. On the other hand, organizations that have an MTO system first receive customer requests and produce based on the existing order; Toyota is a clear example of this type of system. Determining and implementing the inventory control system in MTS, MTO or a combination of the two systems will be different.

One of the types of inventory control systems is material requirements planning or MRP, which is actually intelligent information and decision-making system that determines the type of raw materials, their amount, and their supply time in order to realize the production plan of products and WIP[3] items in a production system. The inputs of this model include BOM[4], MPS[5], lead time, and inventory file. The outputs of this model are the raw material supply plan as the main output and its sub-outputs include control of consumables items of production plan, financing planning, budgeting, etc. The problem of this research is the correct implementation of the MRP system with the new method of determining the lot size.

Today, with the advent of the Internet and advancement in information technology, new changes have been made in the competitive markets, so that the progress in e-business, e-commerce, transportation networks, etc. has made the gap between MTS and MTO systems smaller and smaller. Despite these special conditions, while the importance of demand management has increased, organizations are forced to consider short lead times and high product quality. Factories and organizations have shown good attention to the issue of inventory control system, revenue management and profitability, to the extent that a lot of research is done and published on this topic in academic discussions, and also the production and sale of software in this field has increased significantly. Due to this noteworthy attention, this background is created that the establishment of a suitable inventory control system is effective in the success of organizations.

If we divide the production costs into three parts of raw materials, wages and overhead in any production system, in the reality of the industry, it can be seen that about 60-90% of the total costs are related to the cost of raw materials. Therefore, in every production system, it is necessary to consider a suitable inventory control system so that, while controlling the costs related to the inventory system, the appropriate inventory, with the right amount, at the right time, at the right price, and with the right quality is provided.

As mentioned before, determining and implementing the appropriate inventory control system plays a key and important role in a production system. One of the types of inventory control systems is material requirements planning, which is able to control a major percentage of the costs of a production system. The subtle point is that the implementation of the candidate inventory control system, if not done correctly, will have a gap and will have the opposite result for the relevant organization. So, knowing the system and solving the implementation gaps will help the success of this project. Therefore, in this study, the special goal pursued is to explain the gaps in the implementation of the material requirements planning model and specify its requirements before implementation. In fact, presenting a new method to determine the accumulated size is the main goal of this article, which naturally will address the secondary goals and subsequent concerns of the author in the correct implementation of the MRP model, because at the heart of MRP lies the following important and vital goals that are in the destiny of profitability of the organization has a significant impact:

Determining the type, amount, and time of purchase of raw materials;
Determining the type, amount, and time of purchase/production of semi-finished products;
Reducing stoppages of production lines due to lack of raw materials; And
Inventory planning and control.

[1] Make to Stock

[2] Make to Order

[3] Work-in-Process

[4] Bill of Materials

[5] Master Production Plan

In this part, according to the studies that have been done from various sources regarding the previous research in this field, the development course of MRP from the beginning to its expansion and various developments will be briefly reviewed.

In 1966, at the American Production and Inventory Control Society (APICS) conference, the first research on material requirements planning was initiated by Joe Orlicky at IBM, Oliver Wight and George Plossl at Stanley Works, and at the 14th APICS conference in 1971, Orlicky and his colleagues in an article entitled "MRP, a hope for the future or the present reality - a case study", they claimed that MRP is far more efficient than point-of-order (ROP) methods. In the 1980s, Oliver Wight proposed the need to integrate production with the planning and control of other production-related resources such as finance and distribution and invented manufacturing resource planning (MRPII) [2].

In a research, Aziz Hamid and his colleagues reported on the use of MRP by 22.7% of Malaysian companies [3]. In an article, Vincent Mabert reviewed the developments and developments of MRP during the years of its formation [2]. The implementation of MRP in a manufacturing company in Greece was investigated by Manthou and his colleagues, and the amount of use of this inventory control system in the relevant company, the problems they face and the benefits of its implementation were explained [4]. The effect of perishable inventory in the decision making of the cumulative determination method in the MRP system was researched by Johnny C. Ho and his colleagues [5]. Fuzzy MRP model considering total fuzzy cost, fuzzy available capacity, and fuzzy demand was developed by Mula [6]. In another study, an algorithm using the branch-and-cut approach to determine the backlog in the MRP system was presented by Mirmohammadi and his colleagues [7]. Continuous MRP model with zero confidence inventory and cumulative determination by L4L method was proposed by Sadeghian [8]. In an article, Diaz-Madronero and his colleagues presented the MRP model with fuzzy lead time with a fuzzy multi-objective integer programming approach [9]. In a research, Cornelis de Man and his colleagues addressed the issue of why Excel software still plays an important role in MRP and production planning and found that this issue is due to the dynamic nature of the MRP model [10]. In another research, a hybrid algorithm of genetic algorithm and forbidden search for MRP system with limited capacity was presented by Sukkerd and his colleague [11]. A technique for planning material requirements and production planning was introduced by Segerstedt [12]. In Ramya et al.'s article, an enterprise software framework for the integration of material requirements planning with workshop scheduling has been developed [14]. In a research, a mixed model of limited chance planning has been developed to solve the MRP problem with mixed uncertainty by Zhu and his colleagues, in which there are both randomness and fuzzy discussions in the decision-making process regarding the determination of the stockpile size. In fact, the purpose of this model is to determine the accumulated size of all items despite random demand and fuzzy capacity limitation [20].

In order to implement the MRP model shown in Figure 2 with the requirements and management insights presented in [26], the agile management framework (Scrum) was used and new algorithms were designed in each part of the system. Then it was programmed using Visual Basic language and user forms and related reports were designed and tested.

The MRP system has a module and this module consists of several components and a special algorithm is designed for each component.

3. 1. Production calendar creation algorithm

As mentioned in the previous sections, one of the important inputs of the MRP model is the master production plan or MPS, which itself also has important inputs, including the production calendar. In fact, for every production that is going to be done in a production system, a production calendar is required in which the following items are specified:

When will be the start date and end date of production?
How many operators are available on each day of this calendar?
Is overtime allowed on holidays or not?
How many days and weeks of the year does each date in this calendar correspond to?

Due to the fact that the production planning period may be monthly or more than one month and the production calendar records will be numerous, therefore, it is necessary to design an algorithm to create a production calendar. For this purpose, the pseudo-code of the production calendar creation algorithm is given in Table 1. In this algorithm, first the start date and the end date of the production calendar are taken from the user, then it is controlled that the end date of production planning is greater than the start date. If the start and end dates of the production calendar are correct, the difference between these two dates determines the number of days in the calendar. Then, in a loop, one day is added to the calendar start date according to the number of days in each iteration, and in each iteration, the date, days of the week, days of the week code, the number of days of the year, the number of weeks of the year, financial year, the number of available human resources, holidays The official calendar, and the status of overtime allowed during holidays, is specified and saved as a production calendar document. Each time this template is called, a new production calendar can be created for MPS input.

Table 1. Pseudo code of the algorithm for creating the production calendar.

Dim StartDate, EndDate, MyDate As String

Get StartDate, EndDate;

If EndDate <= StartDate Then

Display "The end date of the planning should be earlier than its beginning!";

Else

Days = DIFF(StartDate, EndDate);

MyDate = SUBDAY(StartDate, 1, 1);

For i = 1 To Days + 1

MyDate = ADDDAY(MyDate, 1, 1);

InitialDays = Val(WEEKDAY(Left(MyDate, 4) & "/01/01"));

NoOfWorkforce = 40;

Date = MyDate;

WeekDay = WEEKDAY(MyDate, 1);

WeekDayCode = WEEKDAY(MyDate);

DayOfYear = DayOfYear(Left(MyDate,4),Mid(MyDate,6,2),Right(MyDate,2))

WeekCode = Int((DayOfYear + InitialDays) / 7.01) + 1;

Year=Left(MyDate, 4);

Next i

End If

3. 2. Production scheduling algorithm

After the inputs of MPS such as the production calendar, sales plan or budget corresponding to the production calendar, production lines, standard production capacity, number of standard production workforce, etc., it is time to determine the parameters of the products and semi-finished products in the MPS such as the number the formulation or BOM, the duration of the work shift, and the amount of production should be adjusted and finally a decision should be made regarding the manufacture or purchase of semi-finished products. After this stage, it is necessary to schedule the production of products and semi-finished products in MPS. For this purpose, the pseudo-code of the production scheduling algorithm is given in Table 2. At the beginning of this algorithm, the feasibility of MPS is checked, assuming that the amount of time required to produce products and semi-finished products related to a production line does not exceed the nominal capacity of that production line. Otherwise, the MPS parameters must be adjusted again to finally make MPS possible. In the following, the products in MPS, which are arranged according to the production priority, are checked, which production line each one belongs to, and the number of production days required in the production line corresponding to that product and on the corresponding day in the production calendar, as well as the force limit. human will be considered on that day and if that day is not a holiday or overtime is allowed on that day, the corresponding product will be allocated to the corresponding production line and according to the number of days required for production on the corresponding day(s) and the number of manpower required each day will be deducted from the available manpower that day. Considering that each product or semi-finished product in MPS may require more than one day of production, therefore, at the end of the algorithm, the first production time of each product that is scheduled in the production calendar will be allocated to the corresponding product in MPS so that it should be used in MRP calculations to determine the supply time of the relevant product raw materials.

Table 2. Pseudocode of the production scheduling algorithm in MPS with n products and k production line.

Dim ProLineDB (,), ListItems (,), ProCalendarDB (,) As Double

Dim ListItemCount, ProLineFieldNo, TotalProLineNo As Integer

Dim StartDate, EndDate As String

Get StartDate, EndDate, TotalProLineNo, ListItemCount, ProLineFieldNo;

b = Val (DIFF (StartDate, EndDate))

For j = 2 To TotalProLineNo

ProLineDB (j, 7) = 0;

For i = 1 To ListItemsCount

If ListItems (i, 14) = ProLineDB (j, 1) Then

ProLineDB (j, 7) = ProLineDB (j, 7) + ListItems (i, 19);

End If

Next i

If Val(ProLineDB (j, 7)) > b + 1 Then

Display "The number of production days of the production line " & ProLineDB (j, 1) & " is more than the number of days of this production calendar! ";

GoTo L3

End If

Next j

For i = 1 To ListItemsCount

r = 2;

For k = 1 To ProLineFieldNo

If ListItems (i, 14) = ProCalendarDB (1, k) Then

e = 1;

L1:

ProCalendarDB (r, 22) = IIf(ProCalendarDB (r, 22) = Empty, Val(ProCalendarDB (r, 21)), Val(ProCalendarDB (r, 22)));

If e <= Val(ListItems(i, 19)) Then

If UserForm38.ComboBox1 = ProCalendarDB (r, 1) Then

If ProCalendarDB (r, k) = Empty Then

If Val(ListItems(i, 17)) = -1 Or ListItems(i, 17) = True Or ((ListItems(i, 17) = False Or Val(ListItems(i, 17)) = 0) And ProCalendarDB (r, 17) = False) Then

If Val(ListItems(i, 15)) <= Val(ProCalendarDB (r, 22)) Then

ProCalendarDB (r, k) = ListItems (i, 0);

e = e + 1;

ProCalendarDB (r, 22) = Val(ProCalendarDB (r, 22)) - Val(ListItems(i, 15));

ProCalendarDB (r, 23) = UserForm38.TextBox1;

ProCalendarDB (r, 24) = TotalProLineNo – 2;

End If

Else

ProCalendarDB (r, k) = "---";

End If

If UserForm38.ComboBox1 <> ProCalendarDB (r, 1) And r > b Then

Display "For the production line " & k - ProLineFieldNo + 1 & "، MPS is not feasible!";

GoTo L4

End If

r = r + 1;

GoTo L1

End If

Exit For

End If

L4:

Next k

Next i

For i = 2 To b

If UserForm38.ComboBox1 = ProCalendarDB (i, 1) And ProCalendarDB (i, 22) = Empty Then

ProCalendarDB (i, 22) = ProCalendarDB (i, 21);

End If

Next i

For i = 1 To ListItemsCount

For j = 2 To b

For k = 1 To ProLineFieldNo

If ListItems (i, 14) = ProCalendarDB (1, k) Then

If UserForm38.ComboBox1 = ProCalendarDB (j, 1) Then

If ListItems (i, 0) = ProCalendarDB (j, k) Then

ListItems (i, 5) = ProCalendarDB (j, 16);

GoTo L2

Else

ListItems (i, 5) = Empty;

End If

Next k

Next j

L2:

Next i

Display "Production scheduling was done successfully!";

L3:

3. 3. MRP algorithm with a new method of determining the lot size

Due to the fact that the infrastructure for injecting MRP inputs into the model has been prepared in the previous sections, therefore, in this section, the MRP calculation algorithm and the determination of the accumulated size, taking into account the two limitations of the size of the packaging of the goods and the minimum order amount of the suppliers' goods, as described in Table 3 designed. For this purpose, at the beginning of the algorithm, it is controlled that the production program in question is selected so that MRP calculations are done for that MPS because there are separate MRP calculations for each MPS. Next, the amount of production of each product and semi-finished product in MPS, according to the formulation intended for production, is multiplied by the raw material consumption factor in the corresponding BOM and the required amount of raw materials will be obtained. Now, the necessary amount will be deducted from the stock of the warehouse and from the amount of the order on the way of that product to obtain the purchase amount. But the key point is that mostly the suppliers are not able to provide this amount of goods that is obtained at this stage, because the supply of goods is a function of the minimum order quantity that they provide and the size of the product packaging. Therefore, at this stage, if the purchase amount is less than the minimum order amount, it will be adjusted to this amount, and if the purchase amount is more than the supplier's minimum order amount, it should be rounded as a multiple of the product packaging size, until the multiple that is greater than the purchase amount is the shortage. Raw materials do not happen and the production plan is realized. Their supply date is also obtained by deducting the supply time of each raw material from the date of the corresponding product production plan which will be obtained in the previous algorithm. In cases where a raw material is present in the BOM of several products, the earliest date of the production plan of the relevant products will be taken into account and will be deducted from the procurement time of that raw material until the supply date of this product is obtained and realized by the timely supply of the production plan. Therefore, this will be a new method to determine the accumulated size of goods, which, while this issue is not found in the literature, it will also be the most effective method from the point of view of operation, because as mentioned in the previous chapter, the methods in the literature are mainly based on the ordering cost parameters and The maintenance cost depends on the fact that these parameters are not defined in the financial system of production centers.

Table 3. MRP calculation algorithm pseudo code.

Dim MPSDB (,), BOMDB (,), CodingDB (,) As Double

Dim TotalMPSItems, TotalBOMRecords, TotalItemsCoding As Integer

Get TotalMPSItems, TotalBOMRecords, TotalItemsCoding;

If ComboBox1 = Empty Then

Display "First, you must enter the code of the production program!";

GoTo L1

End If

For i = 2 To TotalMPSItems

If ComboBox1 = MPSDB (i, 1) Then

For j = 2 To TotalBOMRecords

If MPSDB (i, 14) = BOMDB (j, 11) And MPSDB (i, 35) = Val(BOMDB (j, 10)) Then

BOMDB (j, 166) = MPSDB (i, 41);

BOMDB (j, 167) = MPSDB (i, 42);

Exit For

End If

Next j

End If

Next i

For i = 2 To TotalItemsCoding

CodingDB (i, 187) = 0;

CodingDB (i, 190) = 0;

For j = 2 To TotalBOMRecords

If BOMDB (j, 166) <> 0 Then

If CodingDB (i, 1) = BOMDB (j, 14) Then

CodingDB (i, 187) = CodingDB (i, 187) + BOMDB (j, 17) * BOMDB (j, 166);

CodingDB (i, 190) = IIf(CodingDB (i, 190) = 0, BOMDB (j, 167), IIf(BOMDB (j, 167) < CodingDB (i, 190), BOMDB (j, 167), CodingDB (i, 190)));

End If

Next j

Next i

For i = 2 To TotalItemsCoding

If CodingDB (i, 187) > 0 Then

Set ListViewItems2 = Me.ListView2.ListItems.Add(, , CodingDB (i, 1));

ListViewItems2.ListSubItems.Add Text:=CodingDB (i, 2);

ListViewItems2.ListSubItems.Add Text:=CodingDB (i, 3);

ListViewItems2.ListSubItems.Add Text:=CodingDB (i, 153);

ListViewItems2.ListSubItems.Add Text:=CodingDB (i, 4);

ListViewItems2.ListSubItems.Add Text:=CodingDB (i, 186);

ListViewItems2.ListSubItems.Add Text:=CodingDB (i, 187);

ListViewItems2.ListSubItems.Add Text:=CodingDB (i, 188);

PurchaseQuantity = CodingDB (i, 187) – CodingDB (i, 186) + CodingDB (i, 188));

ListViewItems2.ListSubItems.Add Text:=IIf(PurchaseQuantity < 0, 0, IIf(PurchaseQuantity < Val(CodingDB (i, 77)), Val(CodingDB (i, 77)), IIf(Application.MRound(PurchaseQuantity, Val(CodingDB (i, 78))) < PurchaseQuantity, Application.MRound(PurchaseQuantity, Val(CodingDB (i, 78))) + Val(CodingDB (i, 78)), Application.MRound(PurchaseQuantity, Val(CodingDB (i, 78))))));

ListViewItems2.ListSubItems.Add Text:=J_SUBDAY(CodingDB (i, 190), Val(CodingDB (i, 76)), 1);

ListViewItems2.ListSubItems.Add Text:=CodingDB (i, 12);

ListViewItems2.ListSubItems.Add Text:=CodingDB (i, 13);

ListViewItems2.ListSubItems.Add Text:=CodingDB (i, 14);

ListViewItems2.ListSubItems.Add Text:=CodingDB (i, 15);

ListViewItems2.ListSubItems.Add Text:=CodingDB (i, 16);

ListViewItems2.ListSubItems.Add Text:=CodingDB (i, 76);

ListViewItems2.ListSubItems.Add Text:=CodingDB (i, 77);

ListViewItems2.ListSubItems.Add Text:=CodingDB (i, 78);

End If

Next i

Display "MRP calculations done successfully!";

L1:

Nowadays, due to the increasing dynamics of environmental and competitive conditions in the domestic and global markets, speed and accuracy in decision-making are very important for managers of organizations. In production organizations, deciding on the supply of raw materials for the realization of the production plan is one of the most important management decisions to the extent that this issue can determine the fate of the organization's profit and loss in a financial year. Because if we divide the production costs of a manufacturing organization into three parts: material cost, wage cost, and overhead cost, according to the type of industry in which the organization is active, about 60–90% of the cost of the operating income of that organization is related to it is the cost of materials. Therefore, it is important for the organization to know the system under its management in a clear and accurate manner regarding the selection of the inventory control system and then regarding the correct and appropriate deployment of the material requirements planning model, so that it can identify and remove the gaps and inadequacies in the deployment of the MRP model. Therefore, in this research, the management insights obtained from the experiences of the authors have been documented so that it can be used by the audience. In the field of material requirements planning and for the purpose of future research, other developments can also take place.

In fact, the lack of a system with industrial engineering approaches and a system thinking that integrates different processes in one system is a gap that is evident in the existing reality of a supply chain and in a way the processes are designed as islands and as if each one is just in a vacuum. They do their work and finally the beneficiaries are not fully satisfied with the output of the work. Therefore, the product development of this thesis and the presentation of an integrated system of supply chain planning with a systemic approach and new algorithms reveal the necessity of conducting this research and solving this gap that even after the design in the form of a doctoral thesis, it can be established and commercialized through the establishment an innovative and knowledge-based company (start-up).

Another topic that has been determined for future research is "providing a material requirements planning system with fuzzy BOM of products". In the existing reality of some production systems, some raw materials and semi-finished products that are present in the BOM of a product do not necessarily have a constant consumption factor and distort the output of the material requirements planning model. For example, glucose, which is a raw material in the BOM of various products such as mayonnaise sauce, ketchup, etc., has a factor called Brix, which can cause its consumption coefficient to vary in the BOM. In order to solve this research gap, according to the factors related to those raw materials, a fuzzy number can be assigned for its consumption coefficient and a new model can be presented in this regard.

Data availability statement

The datasets used and/or analyzed during the current study available from the corresponding author on reasonable request.

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No competing interests reported.

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Material requirements planning system considering batch size and minimum order quantity for items of suppliers

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