Master Production Schedule

MRP I converts the master production schedule (MPS) for end products into a detailed schedule for the availability of the raw material and components used in the end products at the right time in right quantities.

From: Production Planning and Control , 2019

Master production schedules

D.R. Kiran , in Production Planning and Control, 2019

23.1 Introduction

We have seen in the earlier chapters that after aggregate planning, the next step in production planning is the preparation of master production schedules (MPSs). A MPS is a translation of the production planning into schedule charts and details. It expresses the overall plans in terms of specific end items or models that can be assigned priorities. MPS is meticulously drawn up, after the planning stage, to determine when specific products groups will be made, when customer orders will be filled, and what manufacturing capacity is still available for new customer demand. It provides the basic foundation for

1.

Planning for the material and capacity requirements,

2.

Making good use of manufacturing resources,

3.

Making customer delivery promises,

4.

Resolving tradeoffs between sales and manufacturing and

5.

Attaining strategic objectives in the sales and operations plan.

It forms a key link in the manufacturing planning and control interfacing with marketing, distribution planning, production planning, and capacity planning.

Read full chapter

URL:

https://www.sciencedirect.com/science/article/pii/B9780128183649000238

Routing, scheduling, and loading

D.R. Kiran , in Production Planning and Control, 2019

22.13 Levels of production schedules

Routing and scheduling activities are complementary to each other. Routing cannot be planned properly without having a previously designed schedule, and scheduling is impossible without the knowledge of the required routing.

Schedules can be of two types:

•

MPS and

•

detailed schedules.

22.13.1 Master production schedule

The MPS is a meticulously drawn-up translation of the production planning into schedule charts and details in terms of specific end items or models that can be assigned priorities. It expresses the overall plans. While the basic principles of scheduling are dealt with in this introductory chapter, the detailed discussions on MPS are given in Chapter 27, Systems and procedures.

22.13.2 Detailed schedules

Detailed scheduling can be classified into the following, which are also explained in Chapter 27, Systems and procedures:

•

single machine scheduling,

•

flow shop scheduling,

•

job shop scheduling, and

•

continuous process scheduling.

Continuous process scheduling generally applies to 24×7×365 days of continuous processes like oil refining, some process industries like pharmaceuticals, biotechnology, or some specialty chemicals produced in batches, depending upon the demand requirement. While the former involves simplified production planning and control activities, the latter need more meticulous activities, similar to those of manufacturing industries.

Read full chapter

URL:

https://www.sciencedirect.com/science/article/pii/B9780128183649000226

Production Control Systems

James E. Bailey , David D. Bedworth , in Encyclopedia of Physical Science and Technology (Third Edition), 2003

V Materials Requirement Planning, JIT, and KANBAN

Aggregate planning creates master production schedules for finished products. The objective of MRP is to translate those schedules into purchasing and production orders for the entire facility. The material requirements planning system also indicates material and capacity needs for each work center. This system is frequently called MRP-I to distinguish it from a more complex procedure called manufacturing resource planning, or MRP-II. We shall first discuss the MRP-I concept and then show how it is the heart of the MRP-II system.

MRP-I is best presented using a simple product component breakdown, as shown in Fig. 4. This product is a toy circus wagon and the diagram is called a product structure tree. Note that a wheel-axle subassembly is a component of the finished wagon. The numbers in parentheses indicate the quantity of each subcomponent required in the higher level assembly.

FIGURE 4. Assembly tree.

In addition to the product structure tree, MRP-I requires lead time values for each component and a master production schedule for the finished product. Lead time is the time needed to supply some quantity of the component. Suppose, for example, the toy wagon requires 1 day for final assembly while the wheel-axle requires 2 days to assemble and the wheels require 2 days to produce. Suppose 500   wagons are required by the master schedule. It follows that 2000   wheels must be scheduled for production at least 5 days before the completed wagons are due. If, however, there are wheels and wheel-axle assemblies in inventory, more wheels may not be needed. The system must take subcomponent inventory into consideration as it calculates the need for each part.

So far, we have considered a very simple product. Complex products like automobiles have thousands of components and a product structure tree that has many levels. When problems occur in production or with vendor deliveries, schedules need to be adjusted to minimize disruption on the shop floor. Even though MRP calculations are simple, realistic systems require large databases and long run times to keep track of the dynamic production environment. A typical MRP report is given in Fig. 5.

FIGURE 5. Typical MRP-I computer output.

MRP-II stands for manufacturing resource planning and is a system that integrates the MRP-I, marketing, and financial systems with a factory simulator to form a strategic planning tool. MRP-II can be used to study alternative resource levels and market strategies relative to their manufacturing and financial feasibility. Hypothetical marketing strategies are evaluated to determine the possible future demand for various products. These demand estimates are fed through the MRP-I system to determine corresponding requirements at the various work centers. The factory simulator can then be used to determine bottlenecks and idle capacity. If necessary, production capacity can be adjusted and new simulations run. Once a satisfactory capacity level is reached, the financial system is used to estimate the dollar impact of the hypothetical market strategy. In this way, the most cost-effective manufacturing resource plan can be established.

JIT is an acronym for just in time, a philosophy which has the simple objective of having just the right amount of materials available at just the right time. The idea is to carry no more inventory than is absolutely necessary. To make JIT work, several things need to happen. Production levels have to be held constant for weeks at a time. Quality has to be superb so that scrap or rework never hold things up. Machines have to be arranged so that work moves quickly from one machine to the next. Preventive maintenance has to be regularly performed so that machines rarely break down. Tooling has to be redesigned so that changing over from one part to the next can be done very quickly. Suppliers have to be kept well informed so that material arrives exactly as planned. For JIT to happen, the focus of management must change from "get it done any way you can" to "do it right the first time." In other words, material flows quickly, smoothly, and easily through the factory.

KANBAN is a term often associated with JIT. KANBAN means "card" in Japanese and connotes a manual system as opposed to the computerized MRP-I approach to materials management. MRP-I starts with a master schedule for finished products and generates the workorders needed to meet that schedule. KANBAN uses the schedule to drive only the last manufacturing step. Between each step, a small amount of inventory is maintained in a bin or on a cart. A token, or KANBAN, is attached to the bin. When the inventory is taken for use, the token is removed and sent to the upstream supplier. The supplier refills the bins for which he or she has cards. As few KANBANs as possible are used to maintain the smooth flow of work. In this way, material is held to a minimum and generated only as needed.

Read full chapter

URL:

https://www.sciencedirect.com/science/article/pii/B012227410500613X

Manufacturing resource planning (MRP II)

D.R. Kiran , in Production Planning and Control, 2019

31.2 Key functions of MRP II

Key functions and characteristic basic modules in an MRP II system are

1.

MPS

2.

Item master data (technical data)

3.

Bill of materials (BOM) (technical data)

4.

Production resources data (manufacturing technical data)

5.

Inventories and orders (inventory control)

6.

Purchasing management

7.

Material requirements planning (MRP)

8.

Shop floor control (SFC)

9.

Capacity planning or capacity requirements planning (CRP)

10.

Standard costing for effective cost control

11.

Cost reporting for management cost control

Read full chapter

URL:

https://www.sciencedirect.com/science/article/pii/B9780128183649000317

Systems and procedures

D.R. Kiran , in Production Planning and Control, 2019

27.12 Production planning and control systems and formats

The four formats cited in Section 27.3 form the basis for the subsequent PP&C activities like product sequencing, routing, and scheduling. The subsequent sections indicate the systems and formats used by the planning department for the actual PP&C activities.

27.12.1 Annual/aggregate planning

Based on the annual sales forecast submitted 3 months before beginning of the year, the planning department will prepare an assembly-wise manufacturing schedule for the coming year, as discussed earlier Chapter 21 , Aggregate planning, on aggregate planning and master production schedule.

27.12.2 Monthly production planning

On the 25th of every month the production targets for the next month will be prepared based on the sales targets statement and physical stock statement as on 24th and the excepted production and dispatches during the last few days of the month (Fig. 27.7). All the production shops are given the above-detailed assembly-wise program on the first of every month.

Figure 27.7. Monthly production planning chart.

Planning for the press shop: Since the press shop has to work on batch production while the other shops in general have continuous flow, the planning of the machine loading for each press is more critical. The batch quantity for each item may be decided depending upon the inventory carrying costs and setup costs. However, initially we will decide subjectively the batch size between 5000 and 6000, which will be confirmed later by experience.

Read full chapter

URL:

https://www.sciencedirect.com/science/article/pii/B9780128183649000275

Material requirement planning

D.R. Kiran , in Production Planning and Control, 2019

30.1 Why material requirement planning?

As seen in the previous chapters, the basic function of the production planning and control department is to plan the materials required for production either by procurement action or by transfer from the stores to the production shops—that is, to ensure the availability of the right material in the right quantity at the right place at the right time.

Material requirement planning (MRP) is a tool for this computation for the production planning, scheduling, and inventory control functions. MRP converts the master production schedule (MPS) for end products into a detailed schedule for the raw material and components used in the end products. It deals with bringing in the right amount of raw material at the right time to support production and help manufacturing companies better manage their procurement of material to support manufacturing operations.

The detail schedule identifies the quantities of each raw material and component item. It also tells when each item must be ordered and delivered to meet the MPS. MRP is often considered to be a subset of inventory control. It is an effective tool for minimizing unnecessary inventory investment, and MRP is also useful for production scheduling and purchasing of materials.

MRP evolved during the 1960s from the traditional age-old technique of inventory control, and the following can be cited as the broad stages in which MRP-I and MRP-II evolved.

Read full chapter

URL:

https://www.sciencedirect.com/science/article/pii/B9780128183649000305

Safe Cosmetics and Regulatory Compliance: From Burden to Opportunity (Cosmetics as Vectors for Bioterrorists?)

Preston W. Blevins , in Global Regulatory Issues for the Cosmetics Industry, 2009

6.6 Leveraging the Implied Requirements

The theme of this chapter is that product regulatory compliance and the disciplines needed to comply with it can be leveraged into financial "bottom-line" benefit. The contributor to this bottom line is superior inventory management. Inventory is the largest operating cost for most manufacturers. ERP is the overall foundation for leveraging compliance but the specific engine for inventory planning and control is that old faithful tool, MRP. It requires high levels of data accuracy to extract the full benefit from it, just like the high levels FDA record keeping demands. MRP is proven, there is extensive knowledge on how to implement it and effectively use it. It can produce an excellent ROI as a study by Clemson University has shown. We will discuss the Clemson study later in Section 6.7.

According to the APICS Dictionary (12th edition [3]), MRP can be defined as:

A set of techniques that uses bill of material data, formulation data, inventory data, and the master production (shipping) schedule to calculate requirements for materials. It makes recommendations to release replenishment orders for material. Further, because it is time-phased, it makes recommendations to reschedule open orders when due dates and need dates are not in phase. Time-phased MRP begins with the items listed on the MPS (shipping schedule) and determines (1) the quantity of all components and materials required to fabricate those items and (2) the date that the components and material are required. Time-phased MRP is accomplished by exploding the bill of material and formula, adjusting for inventory quantities on hand or on order, and offsetting the net requirements by the appropriate lead times.

Note: The italicized insertions are by the author and are intended to clarify the definition for those not involved in manufacturing operations.

Figure 6.5 highlights MRP's role in the process-batch ERP framework.

Figure 6.5. MRP is a key to successful ERP implementation.

APICS-certified practitioners know and understand the underlying calculating logic for MRP, but the majority of small-to-medium sized manufacturers do not and it is hoped that they will read this chapter and take the appropriate action.

The logic of MRP is designed to calculate time-phased requirements based on actual, or a combination of actual and planned demand. Incoming demand can come from the Master Production Schedule (MPS) or directly from customer orders. It is designed to balance supply and demand. The information needed is:

•

The demand item

•

Its current inventory

•

Current time-phased open commitments

•

Its estimated lead time

•

Its recipe and bill of material

•

Current inventory status of the ingredients needed

•

The current time-phased commitments for each ingredient

•

The lead time for each ingredient

•

Time-phased work-in-progress orders for each ingredient

•

Time-phased purchase orders for each ingredient

MRP takes all this data from the ERP database (see the green graphical representation in Figure 6.5) and calculates:

•

What is needed?

•

How many?

•

When it should arrive in inventory?

•

When the replenishment activity should begin?

Read full chapter

URL:

https://www.sciencedirect.com/science/article/pii/B9780815515692500129

Business process design models and concepts used in operations systems

In Practical E-Manufacturing and Supply Chain Management, 2004

4.2.5 Drum-buffer-rope tool

Drum-buffer-rope (DBR) is the TOC production planning methodology. The traditional DBR model is designed to regulate the flow of work-in-process (WIP) through a production line at or near the full capacity of the most restricted resource in the manufacturing chain. To achieve this optimum flow, the entry of work orders into production is synchronized with the current production rate of the least capable part of the process, referred to as the capacity-constrained resource (CCR). The production rate of this CCR is typically likened to the rhythm of a drum, and it provides the pace for the rest of the system. The rope is essentially a communication device that connects the CCR to the material release point and ensures that raw material is not inserted into the production process at a rate faster than the CCR can accommodate it.

The purpose of the rope is to protect the CCR from being swamped with WIP. To protect the CCR from being 'starved' for productive work to do, a time buffer is created to ensure that WIP arrives at the CCR well before it is scheduled to be processed.

•

The drum: The drum in DBR is the constraint. According to DBR, non-constrained resources should be subservient to the constrained ones.

•

The buffer: A time/material buffer is used to avoid disruptions in the production process. These disruptions can be because of breakdowns, longer setup times, delays by suppliers and so on. Some companies also use shipping buffers to enhance on-time deliveries.

•

The rope: A schedule is executed to release either materials or jobs into the system. The basic aim of the schedule or the rope is to ensure that all workstations are stretched to perform at the speed of the drum.

An underlying principle of TOC is that manufacturing to firm orders with defined due dates is the most desirable situation possible, and preferable to manufacturing to stock. To that end, applying traditional DBR starts with some desired master production schedule (MPS) that includes firm customer orders with delivery due dates. Next, the existence of an internal physical resource constraint is verified. The identification of such a constraint (CCR) can be supported by computerized capacity analysis, but should be validated by production management.

Immediately, there are two distinct possibilities:

1.

There is no capacity constraint currently active, or

2.

A definite capacity constraint is identified.

The DBR method strives to achieve the following:

•

Very reliable due-date performance

•

Effective exploitation of the constraint

•

As short response time as possible, within the limitations imposed by the constraint(s).

Conceptually, the three main process steps of DBR are:

1.

Identify the constraint – the plan for exploiting the capacity constraint (the 'drum').

2.

Determine the amount of buffer to ensure that the drum is not idle on the basis of past experience – Protection against 'murphy' (the 'buffer' expressed in time rather than in things that are stocked somewhere).

3.

The schedule is determined by working backwards from the due date of the job – A material release schedule (the 'rope') that protects the shop floor from excess WIP and priority confusion. The DBR assumes that true material constraints are very rare and proper inventory management should ensure material availability as required.

The DBR scheduling results in flexible batch manufacturing, less investment in inventory and a reduction of work-in-process inventory.

DBR when no CCR is active

When no CCR is active, there is no reason why all the firm orders should not be delivered on time. The list of those orders constitutes the 'drum', which is really the master production schedule (MPS).

DBR when a CCR is active

When a CCR is confirmed to exist, a finite capacity schedule is generated for it, based on the preliminary MPS. The MPS is subsequently revised, based on the limitations imposed by the CCR. The new MPS and the detailed schedule for the CCR constitute the Drum.

In this situation, three buffers are established as a protection mechanism against variability ('murphy'):

•

A shipping buffer: This is a liberal estimation of the lead-time from the CCR to the completion of the order or the lead-time from raw materials to completion.

•

A CCR buffer: The CCR buffer is a liberal estimation of the lead-time from raw material release to the site of the CCR.

•

An assembly buffer: This is a liberal estimation of the lead-time from the release of raw materials to a process step where parts that do not use the CCR are assembled with parts that do.

The rope is the schedule for release of materials as dictated by the three buffers. The three schedules are the typical output of DBR planning. The rest of the resources are not specifically scheduled. They are directed to process any order arriving to their site as fast as possible. The rope ensures that no order is released to the manufacturing floor until the CCR or shipping buffer times.

A simplified DBR (S-DBR)

To apply S-DBR, the presumption is that the company is not currently constrained by any internal resource. In other words, the market is the overarching constraint for the company.

When the market is clearly the constraint, the combination of the simplicity of DBR planning with the highly focused control afforded by buffer management, results in full subordination of operations to sales (the constraint). However, when a CCR begins to emerge the following significant changes are observed:

•

The decreasing capacity of the internal resource constraint may limit the company's ability to respond to the market. Some orders may not be delivered on the required dates. To keep this condition from deteriorating even further, either some of the market demand must be reduced, or capacity must somehow be increased.

•

The actual lead-time from raw material release to order completion and shipping increases significantly.

•

Every unit of product needs to pass through two buffers covering various non-constraint operations (assembly and shipping) rather than just one.

•

Buffer management now includes three buffers, each of which must be monitored and managed. This can create conflicts when a single resource must expedite different orders for different buffers.

The basic assumption underlying S-DBR are as follows:

Basic assumption No. 1

The market dictates certain requirements that a company must meet, otherwise, demand for the company's product or service will diminish and perhaps vanish completely in the future. These requirements imposed by the market sometimes conflict with full exploitation of an internal constraint (CCR).

Basic assumption No. 2

A small change to the actual processing sequence at an internal constraint does not have much impact on overall system performance.

Differences between traditional DBR and S-DBR

There are some key differences between traditional DBR and S-DBR:

Level of throughput

Traditional DBR is capable of squeezing more throughputs out of the CCR in certain peak demand periods, due to the detailed CCR schedule.

Customer satisfaction

The role of the shipping buffer in S-DBR is more dominant than in traditional DBR. When the shipping buffer is added to the CCR buffer, the protection of promised due-dates is less effective. This is essentially the same phenomenon that causes a critical chain project completion buffer to be more effective than a number of buffered intermediate points.

Focus

Traditional DBR is usually focused on the internal resource while S-DBR is focused on the market demand.

Lead-time Having one buffer, rather than three, enables S-DBR to achieve shorter lead-times. The accumulation of protection is always more effective than spreading it.

In most situations market demand fluctuates, and so dealing with peak and off-peak demand is frequently required. Assuming we cannot fully level the load on a CCR throughout the year, we can conclude that the CCR is active only around the peak period, and the market demand is the sole active constraint in any off-peak periods.

Shifting from three buffers to one buffer and then back to three buffers again represents a huge policy change for traditional DBR, with significant ramifications for management. For this reason, in most cases organizations using traditional DBR would regard the CCR as a constraint even in a period of low demand. This produces suboptimal results (longer delivery times) in off-peak periods. The S-DBR is able to shift smoothly between peak and off-peak periods, as the main focus of planning and control have not changed (satisfaction of the market).

Support from common information technology (IT) packages: S-DBR is much easier to plan and control with common MRP systems. In fact, specialized DBR software packages are not really needed, since MRP systems can be adjusted to support S-DBR. This can be a real benefit to companies that already have MRP systems but might be unable or unwilling to invest in specialized DBR software.

Read full chapter

URL:

https://www.sciencedirect.com/science/article/pii/B9780750662727500075

Introduction to manufacturing

Peter Scallan , in Process Planning, 2003

1.8 Manufacturing organizational structures

In Section 1.4, it was explained that the sub-systems of the manufacturing system are based on the functions or departments within the organization. The organization of these functions plays an important role in the achievement of the system objectives. Therefore, once the functions required have been identified, the most appropriate organizational structure must be employed to help achieve the system objectives.

1.8.1 Typical functions in a manufacturing organization

Although every manufacturing organization is unique in some respect, there are six broad functions that can be identified in almost any manufacturing organization. These are sales and marketing, engineering, manufacturing, human resources, finance and accounts and purchasing. The general responsibilities of these functions are as follows:

Sales and marketing – this part of the organization provides the interface with the market. The main responsibilities of this function are to ensure a steady flow of orders and consolidate and expand the organization's share of the market. Typical sub-functions might include sales forecasting, order processing, market research, servicing and distribution.

Engineering – typically under this functional heading the sub-functions would include product design, research and development (R&D) and the setting of specifications and standards. The level to which R&D is carried out will depend on the product. For example, in high-tech products, R&D will play a major role in determining the use of materials and processes and future product design.

Manufacturing – the diversification of the manufacturing function will depend very much on the size of the organization. Typical sub-functions might include:

•

Production planning with responsibility for producing manufacturing plans such as the master production schedule (MPS) and the materials requirements plan (MRP).

•

Quality assurance whose job it is to ensure that products are being made to the required specification.

•

Plant maintenance with the responsibility of ensuring that all equipment and machinery is maintained at an appropriate level for its use.

•

Industrial engineering whose responsibilities include the determination of work methods and standards, plant layouts and cost estimates.

•

Manufacturing engineering whose responsibilities includes manufacturing systems development, process development, process evaluation and process planning.

•

Production/materials control who coordinate the flow of materials and work through the manufacturing plant (work-in-progress). Stores will usually be included in this function.

•

Production whose responsibility it is to physically make the product.

Human resources – this is again a broad heading that typically will include sub-functions such as recruitment, training and development, labour relations, job evaluations and wages.

Finance and accounts – the main responsibilities of finance include capital financing, budget setting and investment analysis. Accounts generally deal with the keeping of financial records including cost accounting, financial reporting and data processing.

Purchasing – this primarily involves the acquisition of materials, equipment and services. They must ensure that the above support the manufacturing capabilities by satisfying their supply need. They must also ensure the quality and quantity of supplies through vendor rating.

1.8.2 Types of organizational structure

How the above functions are represented within an organization will depend mainly on the size of the organization. For example, in a small organization some of these functions may be combined such as purchasing and finance and accounts. However in a large organization there may be further diversification of functions, creating more departments such as sales and marketing being large separate departments. How these are organized will also depend on a number of factors. These will include, among others, the size of the organization, how many facilities/locations there are within the organization, the complexity of the products being manufactured and the variety of products manufactured. Finally, the 'style' of management employed, that is, centralized or decentralized, will be a major factor in the type of structure employed. In an organization with a centralized structure, management responsibility and authority is held within the upper levels of the organization. However, in a decentralized structure, some of the responsibility and authority is pushed down to the lower levels. This allows decisions to be made at the levels most affected by them. It also frees senior management from the day-to-day decision-making. Taking all of the above into account, there are three basic organizational structures employed in manufacturing (Coward, 1998):

•

a functional structure;

•

a product structure;

•

a matrix structure.

Functional structure

The most common structure employed is that which organizes the departments around the functions within the organization, that is, a functional structure. This type of structure also tends to be hierarchical in nature as shown in Fig. 1.5. The main advantage of this type of structure is that the knowledge and expertise of each function is concentrated in one part of the organization. However, in larger organizations with a functional structure, there tend to be conflicts of interest between departments, based on conflicting departmental objectives. For example, while marketing and production might want high inventories to ensure availability of product and continued production, finance will want to minimize inventories to minimize costs. Finally, a functional structure usually employs a centralized style of management.

Figure 1.5. A functional structure
Product structure

Many large manufacturing organizations produce a diverse range of products. In such organizations, it is common to employ a structure based on the products manufactured, that is, a product structure. This generally means splitting the organization into product divisions, all of which incorporate the functions required to manufacture the specified product. However, indirect functions such as sales and marketing, finance and accounts, human resources and purchasing will generally be shared across the group. Each division will also tend to act as an autonomous business unit. The main advantage of this approach is that the required product expertise is incorporated into a single part of the organization. However, the main disadvantage is the duplication of functions across divisions as illustrated in Fig. 1.6. Finally, product structures tend to employ a decentralized management style.

Figure 1.6. A product structure
Matrix structure

In essence, a matrix structure is an attempt to obtain the benefits of both functional and product structures. This is based on one manager being responsible for functions and products in one area and is similar to the product structure in this respect. However, the main difference is that the matrix groupings are temporary. This is to allow the resources for each group to be changed. This is based on a continuous review of resources carried out to ensure that the allocation of resources is appropriate for each group. Ultimately, this gives the matrix structure more flexibility than the product structure. Finally, the management style employed in a matrix structure is decentralized. An example of such a structure is illustrated in Fig. 1.7.

Figure 1.7. A matrix structure

1.8.3 Organizational management levels

Within all manufacturing organizations there are usually three distinct levels of management. These are referred to as strategic, tactical and operational management.

Strategic level – this level is usually associated with senior management. This involves the setting of short- and long-term business objectives that will give the organization a competitive advantage over other similar organizations.

Tactical level – this level is associated with middle management. The main function of this level is to develop the plans by which the business objectives can be met using the organization's resources.

Operational level – this level is the frontline management and the main function of this level is to ensure the everyday operations are planned and monitored.

Read full chapter

URL:

https://www.sciencedirect.com/science/article/pii/B9780750651295500027

Key factors for operational performance in manufacturing systems: Conceptual model, systematic literature review and implications

Marcelo Battesini , ... Diego Augusto de Jesus Pacheco , in Journal of Manufacturing Systems, 2021

3.3.2 Operational decisions

Our results show that decisions related to demand management and supply chain [N] directly impact the activities of production planning and control [O]. For example, demand management seeks to coordinate and control the demand sources so that the supply chain performs efficiently, and the product is delivered on time [7]. On the one hand, the supply chain and logistics share the same production and operation objectives [72]. On the other hand, the logistics function (the flow of products and information in businesses) may be considered a more traditional and specific concept than supply chain, which refers to a broader integration and coordination of suppliers, manufacturers, and consumers that is integrated with production planning [69].

The literature also reinforces that MS development should be planned to meet demand and limited to the installed capacity. Moreover, demand should be independent and variable over time. Consequently, the balance between demand and capacity is crucial to MS performance since the system loses revenue when demand is greater than the installed capacity. The opposite, installed capacity higher than demand, results in idleness. As can be noted, production planning and control [O] encompasses the integration of demand, capacity, and the resources available to meet demand. This concept includes planning (when), loading (how much), sequencing (in what order) [P], monitoring (following the planned sequence), and controlling (pulled or pushed) [49 ]. These activities involve preparing the aggregate production plan and the master production schedule [ 5].

Production planning (short-term) involves complex OPM decisions that are not solvable with humanly intuitive solutions. Instead, they demand computational systems, simulation techniques, and artificial intelligence algorithms applied to combinatory problems [62]. Therefore, production programming, loading, and sequencing [P] are usually performed based on systems such as MRP II/ERP, Kanban, and Drum Buffer Rope (DBR) [4,62]. MRP II/ERP systems use backward planning based on the expected date of conclusion. Kanban balances production by assuring that each station produces the same amount as previous stations; it is a useful tool for simplifying administrative tasks on the shop floor. However, Kanban is not viable when orders are unpredictable or infrequent [71], e.g., non-repetitive productions or engineering to order systems. Conversely, synchronized manufacturing (DBR) uses forward planning by allocating orders compatible with the system's capacity (bottleneck) and adopting processing and transference batches with varied sizes throughout the flow [7].

Our conceptual model also shows that operational decisions involve the definition of production batches (total items manufactured in sequence without setup) and transference batches (quantity of items moved through the process) [Q]. This process allows to identify the number of batches and the total time with setups. The literature also shows that an adequate batch size balances the total fixed costs associated with machine preparation, process inventory [7,62], and material movement [72]. In this regard, MRP systems provide several decision tools for determining the adequate economic lot size [73]. In contrast, in the lean production system, the total work in process inventory is reduced due to the adoption of smaller production batches. This is possible by reducing the number of setups [5], even with the production of a diverse mix of items [71]. On the other hand, in DBR management, the bottleneck is the key variable for optimizing setup time and defining production batch sizes, which can vary (bigger in the bottleneck resource) and sometimes differ from the transfer batch size [7,68].

Therefore, the production flow [R] is the result of several operational decisions and determines the finished production [AA] (throughput and makespan). Consequently, the measures of MS's operational performance should be designed to generate flow. Flow is movement over time, and the main goal of OPM is to optimize the production flow in MS [68,71,74]. Thus, the notion of production flow is related to global efficiency and is equivalent to lead time [68]. Lead time [S] is defined as the time between the release of the production order and the moment the product is available [62]. It can also be defined as the time used to complete a task from the beginning to the end; thus, the higher the lead time, the higher the WIP [5]. Therefore, the system's flow should be balanced based on the resource with constrained capacity [43]; the company should aim at balancing the product's flow in the system (global optimal) instead of the capacities (local optimal) [7].

According to the literature, the average lead time (LT) of a system is calculated by LT = WIP*tp, or the number of WIP units (WIP, un) and their processing time (tp, time/un) [7,49], where tp is the inverse of the processing rate (un/time). This expression is equivalent to the fundamental law of PS engineering, Little's law [T] for queueing systems [41]. The law establishes that, under stable conditions, (stable inputs and outputs = steady state) [75]: W = L/λ= L*t, where the average time of a unit in the system (W) can be estimated based on the average number of units in the system (L, in un) and the arrival rate (λ). The arrival rate can be calculated by the inverse of the average time (t) between two consecutive arrivals.

Our conceptual model demonstrates that the processing rate expresses an established system capacity that influences WIP and LT. Therefore, it is a consequence of previous decisions regarding production management. In particular, it is a consequence of strategic decisions related to the technological capacity of establishing cycle and setup times and the decision by batch sizes (production and transfer batches). This assumption is corroborated by [5], which claims that costs related to WIP are tolerable to reduce setup costs, including the cost of idle equipment.

These outcomes suggest that operational decisions determine the MS routine and must focus on achieving an optimized production flow. Flow is movement, it is dynamic, and is related to the passage of discrete parts manufactured at the MS. While the MS components are usually static. In addition, operational decisions involve a continuous change over time between demand and available capacity. These changes are conditioned by previous strategic decisions and strongly influenced by the management philosophy. In this sense, operational decisions can be more easily adjusted because they depend on soft technologies (e.g., information processing and relationships between individuals). In contrast, strategic decisions are determined by the MS and thus incorporate hard technologies. Besides, the model describes supply and production planning (e.g., production and transfer batch sizes) as key factors at the operational level. Such an assumption defines a causal direction to Little's law by identifying WIP and LT as outcomes and the processing rate as a key factor that results from OPM decisions. Lastly, we found that this causal direction should form the basis for theoretical or empirical studies on MS performance by using WIP and LT as results (variables to be observed) that are caused by the processing rate and the factors that determine it.

Read full article

URL:

https://www.sciencedirect.com/science/article/pii/S0278612521001291