Optimizing the production of the sub-assemblies in a high-mix-low-volume environment

(1)

high-mix-low-volume environment

Niklas Hantila

School of Science

Thesis submitted for examination for the degree of Master of Science in Technology.

Vantaa 18.11.2022

Supervisor

Prof. Fabricio Oliveira

Advisor

MPhil Margaretha Talus-Suoniemi

(2)

(3)

Author Niklas Hantila

Title Optimizing the production of the sub-assemblies in a high-mix-low-volume environment

Degree programme Mathematics and Operations Research

Major Systems and Operations Research Code of major SCI3055 Supervisor Prof. Fabricio Oliveira

Advisor MPhil Margaretha Talus-Suoniemi

Date 18.11.2022 Number of pages 65+7 Language English Abstract

Lean principles have been widely adapted in different industries. However, the high-mix-low-volume (HMLV) industries have not adopted the benefits of lean due to the complexity of the environment. In this thesis, we propose a framework for controlling the manufacturing of sub-assemblies between factories.

The research questions aiding in creating the framework are 1) How should manufactured sub-assemblies move around the factories and what types of production planning should be used for sub-assemblies in Vaisala Oyj? 2) What is the optimal system for optimizing make-to-stock (MTS) sub-assemblies in an HMLV environment?

The research methods include a literature review on the topic and analyzing the current practices in the manufacturing sites in Vaisala.

With the aformentioned research methods, new movement methods and production triggers were determined. Movement methods are a concept for achieving more efficient flow for sub-assemblies in the factories. The production triggers were determined into assembly-to-order and MTS. The MTS category has three sub- categories: visual, enterprise resource planning (ERP) and abnormal triggers. The thesis focuses on developing the MTS ERP trigger, which follows a periodic (R_n, Qn) policy, in which the R_n is the reorder point for sub-assembly n and Q_n is the order size for sub-assemblyn. The equations used for (R_n, Q_n) policy were modified for sub-assemblies in the HMLV environment. To find the best values for (R_n, Qn) policy, hyperparameters and machine learning were used with inventory simulations.

The inventories aimed to decrease the inventory levels, variation and ensure the availability of sub-assemblies. With these boundaries, the optimal hyperparameters were found and evaluated. The optimal (R_n, Q_n) policy values for the next three months were able to be calculated from the demand data and used in triggering the production of these sub-assemblies.

The thesis constructed working production triggers, which were piloted on the shop floor. The piloting showed that the production triggers work and these triggers were implemented on the rest of the sub-assemblies in Vaisala.

Keywords High-mix-low-volume, sub-assembly, manufacturing, inventory control, production control, simulation, machine learning

(4)

Tekijä Niklas Hantila

Työn nimi Osakokoonpanojen tuotannon optimointi korkean sekoituksen ja pienen volyymin ympäristössä

Koulutusohjelma Matematiikka ja operaatiotutkimus

Pääaine Systeemi- ja operaatiotutkimus Pääaineen koodi SCI3055 Työn valvoja Prof. Fabricio Oliveira

Työn ohjaaja MPhil Margaretha Talus-Suoniemi

Päivämäärä 18.11.2022 Sivumäärä 65+7 Kieli Englanti

Tiivistelmä

Lean-periaatteita on sopeutettu laajasti eri toimialoilla. High-mix-low-volume (HMLV) teollisuus ei kuitenkaan ole omaksunut leanin etuja ympäristön monimutkaisuuden vuoksi. Tässä työssä ehdotamme viitekehystä osakokoonpanojen valmistuksen ohjaa- miseksi tehtaiden välillä.

Viitekehyksen luomisen tutkimuskysymykset ovat 1) Miten valmistettujen alirakenteiden tulisi liikkua tehtaissa ja millaista alirakenne tuotantosuunnittelua Vaisala Oyj:n tulisi käyttää? 2) Mikä on optimaalinen järjestelmä valmistaa varastoon (MTS) alirakenteita HMLV-ympäristössä? Tutkimusmenetelminä käytettiin aiheeseen liitty- vää kirjallisuuskatsausta ja Vaisalan tuotantopaikkojen nykykäytäntöjä.

Tutkimusmenetelmillä määritettiin paremmat logistiset menetelmät ja tuotannon aloittamiskynnyspiste alirakenteille. Logistiset menetelmät ovat konsepti tehokkaam- man virtauksen aikaansaamiseksi tehtaiden alirakenteille. Tuotannon aloittamiskyn- nyspisteeksi määriteltiin kokoonpano tilaustyönä ja MTS. MTS-kategorialla on kolme alaluokkaa: visuaalinen, toiminnanohjausjärjestelmä (ERP) ja muut tavat. Työ kes- kittyy MTS ERP aloittamiskynnyspisteen kehittämiseen. MTS-alikokoonpanojen ERP aloittamiskynnyspiste noudattaa säännöllistä (R_n, Q_n) käytäntöä, jossa R_n on tilauspiste alikokoonpanollen ja Q_n on alirakenteen n tilauskoko. (R_n, Q_n) käytän- nössä käytettyjä yhtälöitä muutettiin alirakenteille HMLV-ympäristössä. (R_n, Q_n) käytännön parhaiden arvojen löytämiseksi tapahtui simuloimalla varastoja, jossa käytettiin hyperparametreja ja koneoppimista. Varaston simulaatioiden tavoittee- na oli vähentää varastotasoja, vaihtelua ja varmistamaan alirakenteiden saatavuus.

Näillä tavoitteilla löydettiin optimaaliset hyperparametrit, joita arvioitiin lopuksi.

Optimaalisilla hyperparametri arvoilla voitiin laskea kysynnän avulla tilauspisteet ja tilauskoot seuraavalle kolmelle kuukaudelle, joita voidaan käyttää alirakenteiden tuotannossa.

Opinnäytetyössä rakennettiin toimivat tuotannon aloittamiskynnyspisteet, joita pilotoitiin tehtaissa. Pilotointi osoitti, että tuotannon laukaisimet toimivat ja nämä laukaisimet toteutettiin muihin alirakenteisiin Vaisalassa.

Avainsanat Korkea sekoitus- matala volyymi, alirakenne, tuotanto, varastojen hallinta, tuotannon hallinta, simulaatio, koneoppiminen

(5)

Preface

On my first day of university, I heard talk about the master’s thesis all around and the master’s thesis seemed to be extremely far away and scary. The student years ran by fast and I began the thesis work on the 1st of June in 2022. I was a little scared of the thesis due to the horror stories I heard from the previous years and as soon as I started the thesis, I found out that working on the thesis is enjoyable and challenging. Tackling a problem in which the results are unknown and course assistants are not verifying if the calculation was done correctly. The time passed quickly and my thesis was ready within the schedule.

In my second year of university, I was introduced to the world of optimization, which arose my interest towards mathematically optimizing genuine real world problems. The optimization lectures were held by none other than Prof. Oliveira, who was luckily able to supervise my thesis on optimization. I would like to thank you for the interesting lectures and for supervising my thesis.

The thesis was conducted on Vaisala Operations, so I would like to thank every- body who contributed towards my thesis. The planning team have had a major role in shaping the thesis and they are the ones who get the most benefit out of this.

Everyone who read my thesis from Vaisala, thank you for reading and commenting on the thesis. Lastly from the Vaisala, I would like to thank my advisor Margaretha Talus-Suoniemi (Ia) for guiding me and emphasizing the results of the thesis. Also thank you Ia for your very fast replies to emails and messages.

Lastly, I would like to thank my family. Erja and Isto, thank you for helping with the thesis and supporting me through the thesis work. The insights regarding what should be raised in the thesis helped me on perceiving the results. Thank you Julia for helping me with the language and proofreading the thesis. The written language is not my strongest element, so it was a huge help.

Vantaankoski, 18.11.2022

Niklas S. Hantila

(6)

Abbreviations

ATO Assembly-to-order

BPR Business Process Reengineer DBR Drum-Buffer-Rope

ERP Enterprise Resource Planning HMLV High-Mix-Low-Volume

JIT Just-In-Time

LMHV Low-Mix-High-Volume MTS Make-to-stock

PPC Production Planning and Control QC Quality Control

RQ1 Research Question 1 RQ2 Research Question 2 TMC Toyota Motor Company TPM Total Productive Maintenance TPS Toyota Production Systems TQM Total Quality Management VATO VAO Global Manuf ATO VMRP VAO Manuf MRP

VSM Value Stream Map WIP Work in Process WLC Work Load Control

(9)

1 Introduction

Customers desire products that are configured according to their preferences. To fulfil customer desires, companies offer products that can be configured based on the needs of customers. To be able to respond to customer needs, companies have to be able to produce the products according to the desired configurations. Usually, a large variety of items are required in production and the volumes of the items produced changes over time. This creates what we call a high-mix-low-volume (HMLV) environment, in which the variety of the products is large and the volumes are low.

Lean principles have only been partially accomplished in the HMLV environment.

This is due to the fact that the challenges of the HMLV environment differ significantly from the challenges of the low-mix-high-volume (LMHV) environment in which lean principles are well established. The lean principles were developed for the LMHV industries, in which the production is stabilized and predictable. This is not the case in HMLV industries, in which the production is dynamic and not as predictable. The different existing lean tools may to some extent function in the HMLV environment, which generates a need for new lean tools in the HMLV environment. The current HMLV frameworks are based on individual lean tools, which do not function well in the HMLV environment (Tomasevic et al., 2021).

Controlling the production of sub-assemblies through inventory control does not have a well-established framework within the HMLV environment according to Tomasevic et al., (2021). There is a notable amount of inventory control frameworks that work with purchasing inventories, but there is hardly any inventory control regarding buffers in manufacturing. Fortunately, inventories are extremely close to buffers and the principles of inventory control can be applied to manufacturing buffers. The changing volumes and production times for sub-assemblies in the HMLV environment can cause difficulties in inventory control and a new framework needs to be constructed that follows the lean principles.

1.1 Scope and objective

The objective of this thesis is to solve the current problem of unclear movements and planning of sub-assemblies in Vaisala. There is no standardized movement of sub-assemblies in Vaisala, which causes confusion on the shop floor. The planning of sub-assemblies has not been standardized and there are no clear definitions for the planning of the sub-assemblies. Make-to-stock (MTS) sub-assemblies do not utilize different inventory controls or the control values are outdated.

The thesis focuses on the sub-assemblies in the instrument and weather factories of Vaisala. The thesis considers the sub-assemblies that are used by consuming production cells in the instrument and weather factories. This outlines the sub- assemblies that are only used by the producing production cells.

The objective can be solved with the following research questions:

Research question 1 (RQ1): How should manufactured sub-assemblies move around the factories and what types of production planning should be used for sub- assemblies in Vaisala Oyj?

(10)

1.2 Structure of thesis

The thesis is organized as follows: Chapter 2covers the literature review. Chapter 3 examines the general setting of the current practices for sub-assemblies. Chapter4 defines new methods which will answer RQ1. Chapter5 presents the experimental setting and results which will answer RQ2. Chapter6 evaluates the application to a factory setting and discusses imperfections. Chapter 7presents the conclusions and future research possibilities.

(11)

2 Literature review

This literature review consists of four sections, which build up an academic overview to provide guidance and understanding to assist with solving the objectives of this thesis. Section2.1examines lean manufacturing in general, while section2.2 explains the differences between HMLV lean manufacturing and typical lean manufacturing.

Section 2.3 examines the enterprise resource planning (ERP) system capabilities as well as production planning and control. Last, section2.4reviews the optimal reorder points and derives the ordering quantities for sub-assembly parts in a multi-factory setting.

2.1 Lean manufacturing

Lean manufacturing was first established in Toyota Production Systems (TPS) in Japan during the 1950s. Sakichi Toyoda, one of the creators of lean production systems, visited the Ford Production Systems in 1913 and was fascinated by the serial production of Ford Model T. After Toyota Motor Company (TMC) started manufacturing their automobile products, Sakichi implemented some of the techniques he learned from the Ford Production Systems into the TMC manufacturing. After some years of Sakichi’s implementation efforts, Japan as a whole suffered from reduced demand, which resulted in reduced amounts of automobiles and various models being produced in the same manufacturing line in the TMC facilities, (Łukasz Dekier,2012).

Kiichiro Toyoda, one of the two sons of Sakichi Toyoda, understood that to compete with European and American mass production in the automotive industry, Toyota and Kiichiro had to change their methods of production. Kiichiro wanted to create a fast and flexible production system, which would produce customer-specific, high quality and reasonably priced automobiles. He started to do the initial work to implement a Just-In-Time (JIT) system, which strives to increase production capacity and reduce waste during the entire manufacturing process, from raw material to the final product, (Łukasz Dekier, 2012).

Eiji Toyoda, the other son of Sakichi Toyoda, and Toyota engineer Taiichi Ohno visited Ford in the 1950s. They created a new system for the Ford assembly line, which linked the two main pillars for TPS, Jidoka and JIT. The main principle of Jidoka is that there are methods to detect defects in production. With the Jidoka method, production can be paused to remove or fix defects. The other pillar’s principle, JIT, is getting the product quickly through production, to the right place and right on time. Shortly after the visit, Taiichi Ohno created a concept of pull-flow production, which generated as many products as the process was able to produce. It enabled smoothing the over-production in manufacturing processes and reduced waste. This was the birth of lean production, which did not attract any major interest in other Japanese and American companies in 1973. After the reduced general demand for new automobiles in Japan and America, companies noticed the remarkable pull-flow system Toyota had created, (Łukasz Dekier, 2012).

(12)

2.1.1 Basic concepts of lean manufacturing

Lean practices have evolved constantly since it was brought to the attention of other manufacturers besides Toyota. The main focus point of traditional manufacturing is the inventory of systems, which differs from the lean concept. The lean concept treats inventory as a waste in an organization. In lean manufacturing, waste is considered to be anything that does not add value to the final product. Organizations need to understand the fundamental differences between traditional and lean manufacturing, if they want to move towards lean manufacturing and succeed in it (Lee-Mortimer, 2006). In lean manufacturing, the basic principle is that the customer is willing to pay for the value of goods and services which they receive. Customers are not willing to pay for errors (Rawabdeh,2005). The price that defines the manufactured product is derived from the customer’s point of view and not from the manufacturing process.

The lean manufacturing process emphasizes the reduction of waste arising during the manufacturing process (Gupta and Jain, 2013). To reduce waste, lean tool techniques have been developed. Combining different lean tool techniques with the often utilized SWOT (strength, weakness, opportunity and threats) analysis has been proven to be useful. This was used in a case by Upadhye et al. (2013), in the combination of tools and SWOT analysis reduced the waste in the manufacturing process. When these tools are used properly and the implementation has been successful, productivity increases and there is a reduction in Work In Process (WIP) and finished goods (Seth and Gupta, 2005).

Lean, as a whole, should be viewed as a philosophy rather than a set box of tools to be utilized. The main principles and concepts of what can be seen as tools for lean manufacturing are described in the lean philosophy (Gupta and Jain, 2013).

Bhasin and Burcher (2006) interpreted that lean as a tool is too shallow compared to various strategies and tactics within the lean concept. Lean as a tool is also too shallow to implement and sustain any of these strategies, which suggests that lean should be viewed as a philosophy. Also, Moore (2001) agrees with the argument that lean is a philosophy or condition rather than a process. Lean as a philosophy is also confirmed by Taiichi Ohno, who confirmed that the TPS did not happen suddenly, but it took over three decades with a chain of innovations to the stage of TPS (Bhasin and Burcher, 2006).

There is a common misconception about the term lean in organizations, which leads to misunderstandings and failures. Chase (1999) suggested that employees in organizations believe that they are implementing lean but in reality, they are implementing just one or two elements of lean. McNabb and Sepic (1995) have indicated that implementing the lean philosophy into an organization is not an effortless process. Past failures of lean implementations have been blamed on existing organisational culture, which may cause major resistance to the implementation of new ways of thinking. To apply the lean philosophy to an organization, the benefits of lean need to be presented in a way that the employees in the organization will see and experience the improvements effortlessly (Bartezzagni, 1999). In addition to the successful implementation of lean philosophy, Henderson et al. (1999) pointed out that it is essential for the right culture to exist in the organization to enjoy all the

(13)

benefits of lean.

Lean is presented as a philosophy because it attracts more people and they will most likely buy into that belief (Vasilash,2001). Lean needs to be a journey, which evolves rather than a process. If it is seen as a process, then the applier would only achieve the results and not evolve them further (Bhasin and Burcher, 2006).

Elliot (2001) argues that organizations need to live, breathe and guide the aspects of lean. Fundamentally, this means that lean is a mindset that enables one to control a business or process. Liker (2004) describes that companies can implement Toyota’s business philosophies and management principles, which made Toyota successful.

Liker widely talks about "lean learning enterprise" and the way Toyota modified its culture to the changing environment. Liker provided suggestions for organizations adopting lean into their day-to-day business and Hall (2004) highlighted risks relating to the implementation of lean. Specifically, Hall noted that not every company can adopt Toyota’s principles due to the different characteristics of organizations, the processes that the organizations handle and the prevailing cultures.

To maximize the benefits of the lean philosophy, the involvement of suppliers is compulsory (Gupta and Jain, 2013). Lean manufacturing enables continuous improvement of existing processes. Bhuiyan and Baghel (2005) surveyed the continuous improvement of processes from the past to the present. Bhuiyan and Baghel concluded that for an organization to achieve the best possible results, the continuous improvement of processes should utilize different methodologies. These used methodologies include lean manufacturing, six-sigma, lean six-sigma and balanced scorecard. All of these methods assist organizations to reach higher levels of pull production by reducing variability in the system, which then reduced the defects in the production processes (Hopp and Spearman, 2004).

In lean manufacturing, there are considered to be two types of waste. The first type of waste is the obvious waste, which arises out of overproduction, transportation, waiting, inappropriate processing, excess motion, excessive inventory and defects.

The second type of waste is the less obvious waste, which is generated from variability (Gupta and Jain, 2013). When these waste sources are identified, an organization can apply lean principles to diminish waste. Dhamija et al. (2011) defined a lean organization as an organization, that utilizes less material to create their product, less human effort to carry out the same work, less time to develop and design, less space and lower energy usage. These organizations are making high-quality products and services most effectively and economically by focusing on customer demand. To achieve effectiveness, Rose et al. (2011) suggested 17 lean practices that organizations can implement consistently in their organization.

2.1.2 Waste in lean manufacturing

Understanding and eliminating waste in lean manufacturing is essential to practice lean philosophy. Section2.1.1 briefly explained the concepts of obvious waste and less obvious waste. This section will provide a deeper understanding of the different types of waste. There are seven types of obvious waste, which are widely agreed upon in the lean industry, although some practitioners identify eight different waste

(14)

types, due to splitting up one type of waste in two (Dave, 2015). Seven obvious sources of waste are:

Transportation Transportation does not add any value to the end product. For that reason, the lean philosophy aims to eliminate or at least reduce transportation within and outside of the production system. In addition to transportation causing monetary losses, a selected method of transportation can produce quality defects in transit or be simply overpriced. Also, it is worth noting that having a high number work in process (WIP) products in production can lead to additional transportation costs as WIP products may require transportation to a designated storage location. These transportation wastes are often present and not widely recognized in poorly managed organizations (Dave, 2015).

Inventory Inventory is a crucial part to pay attention to in lean manufacturing due to it tying monetary value to physical items that are stored. Having excess inventory ties to monetary value, which means that the organization cannot use the tied monetary value anywhere else. By the principles of lean philosophy, having excess inventory is waste (Dave, 2015).

Motion It is not often understood that there is an excessive amount of waste produced by transportation between workstations. The movement needs to be minimized and roughly 5 % of motion is practical for processing a workpiece (Dave,2015).

WIP (Work In Process) WIP is directly caused by overproduction and waiting.

If there are any imperfections in the production system, it may trigger WIP.

WIP is usually a reflection of other waste that the system has, and it is a valuable indicator that there is possibly obvious or less obvious waste presented somewhere else in the system (Dave,2015).

Waiting time In batch processing, most of the time the products are waiting to be processed. Studies have shown that 90 % of the total production time, goods are waiting to be processed. In some studies, it has been concluded that the waiting time can reach up to 99 % of the total production time. Production cannot recover this lost time after the goods are being processed forward (Dave, 2015).

Overproduction Often organizations consider that overproduction is not waste but it actually can be considered to be waste hidden in plain sight. Overpro- duction happens by producing goods before they are needed. Overproduction is considered to be waste as it produces additional inventory that is not needed at the time of production and causes increased waiting times for the products in question. This often occurs in the push type of production, which is the opposite side of pull production. Pull production is the type of production used in lean manufacturing (Dave, 2015).

Defects Defects are incorrect products, which need to be rejected as they do not conform to the expected predetermined standard of the product (Dave,2015).

(15)

Defects may be caused by differences in supplier quality, transportation, im- proper working environments, unprofessional operators and accidents. Having quality controls in the production processes is crucial to catch defects in the products. In lean philosophy, producing high-quality products is one of the key elements, which is why there need to be quality controls in the production processes to catch any defects. Catching defects in production ensures that the deficient products are not processed forward, and production time is not used to process them forward and generate more waste (Dave, 2015).

Less obvious waste is variability, which is usually not obvious as it is hidden in the process itself (Gupta and Jain, 2013). Eliminating variability completely is almost an impossible task, because processes may suffer from breakdowns, defects, human variability and production planning. The amplitude of variability is higher in the HMLV production compared to LMHV production. HMLV lean production is discussed in more detail in section2.2.

2.1.3 Lean tools

Using the lean tools efficiently is a four-step process in itself. Firstly, one needs to identify the root cause for the waste shown in section2.1.3. After identifying the root cause, data regarding the cause needs to be collected and analyzed. After analyzing the data, the best solution needs to be found to solve the root cause. After finding the best possible solution, implementation of the solution takes place. This process is the key process to removing waste from the processes. Product value is generated from the customer’s point of view, and the margin of the product will increase if there is less waste. When the aforementioned process itself is finished, the process can start again with hopefully different root causes (Dave, 2015).

There are various tools to find and identify root causes, analyze the data, find the appropriate solution and implement it. The most used tools and techniques are:

7-QC (Quality Control) tools QC tools are widely used in the manufacturing industry to solve quality issues. These tools can be categorized into four different stages. The first stage aims to identify any existing root causes. The most commonly used tool in this stage is the Ishikawa tool, which is also known as the cause-and-effect diagram. The second stage focuses on planning how to approach problem-solving. The most used tool is brainstorming. The third stage is considered to be the analysis phase, in which there are five different commonly used QC tools: Pareto, histogram, control chart, check sheets and scatter diagram. The final stage is the small improvements phase and there are no specific QC tools utilized in this stage (Dave, 2015).

Total Quality Management (TQM) TQM was originally a tool but has been evolving into a philosophy. TQM is based on a customer-centric approach, and in its essence, it means that one must satisfy the customer the first time and every time (Dave, 2015).

(16)

JIT (Just-In-Time) The spine of lean manufacturing is JIT. JIT is based on a pull demand model, in which products are produced when they are needed.

In manufacturing operations, the JIT is used in three main areas: purchasing, production and distribution (Dave,2015).

Kaizen A Japanese philosophy, which in its essence means small continuous improvements. The main aim of Kaizen is to decrease small risks, which appear and are often overlooked in larger improvement projects. Kaizen follows the PDCA cycle (Plan, Do, Check, Act), which enables continuous minor improvements after every period (Dave, 2015).

Kanban A widely used synonym for pull production for make-to-stock items is known as the Kanban system. All the items in a production system have a Kanban card attached to them, which is returned to the beginning of the Kanban loop after the good is picked up by another production system or customer. This process allows the production to replace the removed good can begin. Kanban is also widely utilized in the transportation of raw materials and goods. The Kanban system principles can also be used for assembly-to- order (ATO) parts. In such circumstances, the Kanban cards are customized according to the customer-specific requests provided (Roser,2021).

Two-box Kanban A pull production system that utilizes two boxes for storing items. When the first box is empty, it will be delivered to the beginning of the Kanban loop, which starts the production for that item. After the goods are produced, they will be delivered to the consumer. The second box ensures that there are enough items available while the goods for the other box are being produced. Box sizes have a major role in item availability (Roser, 2021).

Value Stream Mapping (VSM) VSM is the most widely used tool in lean manufacturing. It helps with the visualization of station cycle times, inventory buffers between processes, manpower deployment, utilization or uptime of the resources and information flow. VSM visualizes the whole transformation of the raw materials to the finished products. VSM also divides the value-added and non-value-added activities and helps to identify waste in the system. The principles that need to be included in the VSM are (Seth and Gupta, 2005):

• Determination of the value of the product from a customer’s point of view.

• Identification of the value stream.

• Elimination of the seven wastes as identified in section 2.1.2.

• Constructing the workflow and establishing pull production rather than push production.

• Pursuing perfection.

The aforementioned tools are generally considered to be the most used tools in lean manufacturing. Different tools are used for different purposes and finding the best solution for a particular organization or issue might need the utilization of multiple tools together.

(17)

2.1.4 Benefits of lean

It was previously assumed that only large manufacturing companies can benefit from the lean philosophy. Concurrently it has been shown that also small and medium-sized companies can benefit from it (Chavez, 2019). The main benefits from implementing lean philosophy can be divided into two different sectors: typical benefits and hidden benefits (Gupta and Jain, 2013). These two benefit categories can have major positive impacts on the health of organizations (Gupta and Jain, 2013).

Typical benefits consist of waste elimination, financial benefits, cutbacks on reworking, decreased inventory levels and lead time reduction. The hidden benefits consist of fatigue and stress reduction, culture change, reduced time for traceability and improvements in quality and safety.

Hidden benefits do not have a direct connection with the success stories of lean manufacturing, but they have had significant indirect roles in them. Lean manufacturing offers many benefits that are desirable in organizations, but there are some obstacles that lead to opposition to lean implementation. These opposing barriers are poor psychology, financial problems, lack of training and education, demand volatility and lack of responsibility. To tackle these opposing barriers, organizations should put their conservative principles aside and reform their principles with lean philosophy (Gupta and Jain, 2013).

2.2 Lean manufacturing in high-mix-low-volume environ- ment

Lean philosophy has been evolving rapidly and the principles have been spreading fast to different sectors of business. Lean was originally developed for product-focused, MTS and repetitive manufacturing with relatively stable demand for a large volume of most similar products, also known as the LMHV industry (Bragilia et al.,2018). In a stable LMHV environment, lean tools such as for example Kanban work efficiently and behaves pleasantly with an optimized amount of Kanban-cards (Roser, 2021).

Exploring the possibilities of lean implementation in HMLV environments was raised by Hines et al. (2004) and it was predicted that the key topic of lean in HMLV is variability. The characteristics of the HMLV environment differ notably from the LMHV industry, for which lean was originally created. The HMLV environment is characterized by customized products, unpredictable demand and low volumes, which result in varying routing and process times (Rossini et al., 2019). With these characteristics, productive manufacturing becomes a complex process. Olhager and Prajogo (2012) claimed that having an effective manufacturing process is seldom a competitive asset in HMLV industries. Many HMLV organizations want to apply lean principles to their processes, but the prevailing problem with this is that there is insufficient literature on the topic of lean implementation in HMLV industries compared to the existing literature on LMHV industries (Danese et al., 2017). The main issue that has been recognized in the HMLV lean industry is that organizations tend to implement LMHV principles into HMLV environments, which results in an

(18)

even more inefficient process (Tomasevic et al., 2021).

Tomasevic et al.,(2021) have done a systematic literature revision on lean research in the HMLV industry. The research sought to find answers to the following questions in the context of HMLV:

• What is recognized to be lean?

• What is the current maturity of lean?

• What is the scope of lean?

• How does one implement lean?

• What are the practices and tools used?

• What are the future research directions for lean?

If the research question would be in the context of LMHV industries, there would be piles of different answers for these questions. The systematic literature research (Tomasevic et al., 2021) collected all the unique articles from Scopus and Web of Science, which included different synonyms of lean and synonyms of make-to-order keywords. After some filtering, the total amount of articles that were acceptable for analysis was 110. These articles ranged from the year 1975 to 2019. The number of articles started to climb after the year 2010, but the total number of articles stayed relatively low.

2.2.1 Current stage of lean manufacturing in HMLV environment The articles used in Tomasevic et al., (2021) consist mostly of academic papers, which total 106 and the prevailing research methodology is shown in table 2.2.1.

Prevailing methodology Articles

Single case study 39

Simulation 20

Modeling 13

Multiple case study 12

Theoretical 8

Action research 7

Survey 7

Literature review 3

Field research 1

Total 110

Prevailing methodology research. (Tomasevic et al., 2021)

The definition of what is considered to be lean in these articles was not consistent.

41 articles out of 110 articles did not specify any definition of lean in the HMLV context, meanwhile, 54 articles offered a definition for lean in HMLV. These 54 articles,

(19)

which offered a definition, mostly consisted of the same definitions (waste elimination, improved flow, continuous improvement, improved efficiency and improved safety) as in section 2.1. Articles assumed that other authors have the same understanding of what lean is, however, the overview of these showed that there were no common definitions for lean. The traditional lean concepts are used without any extensive discussion (Tomasevic et al.,2021).

The amount of lean models proposed for the HMLV industry in the articles was fairly low. Five articles proposed a model, but four of those proposed the same model with slight variations. After investigating all these articles, the total number of proposed models was two. Muda and Hendry (2002) proposed a model for ATO companies, which contains 14 principles that highlight areas for potential improvement and the strengths of organizations. The other proposed model (Powell et al., 2014) analyzed the evolution of lean principles and argued that new lean principles are required in the HMLV industry. This is due to the assumption that the current principles of lean manufacturing come from the LMHV producers (Tomasevic et al.,2021). The major barrier to implementation of the currently existing HMLV lean models is that they are hard to interpret and implement without translation of an expert of the context (Tomasevic et al.,2021). The model provided by Muda and Hendry (2002) is simpler to interpret than the model of Powell et al. (2014).

Hopp (2008) stated that there are four different stages to becoming a lean organization. Firstly, an organization needs to eliminate direct obvious waste. Secondly, capacity needs to be replaced with inventory buffers. Thirdly, variability must be reduced. Lastly, capacity buffers need to be reduced. To gain an understanding of the maturity of lean in the HMLV industry, the articles in Tomasevic (2021) were analyzed to see if a centre point of lean was in the elimination of waste, reduction of variability, buffer management or combination of these.

Waste Out of the 110 articles examined, 44 focused on obvious waste. The definition of waste differed in the articles. The different waste types included: the seven waste types2.1.2 (Dave, 2015) and anything that does not add any value to the customer. There was no specification or consideration of what is waste.

The different combinations centre points included: waste and variability, waste and buffer, and waste, variability and buffers (Tomasevic et al.,2021).

Variability In Tomasevic et al., (2021), in 19 out of 110 articles, variability was seen as a concern. Variability is seen as a main source of waste and it is affecting a company’s performance negatively (Yin et al., 2018). One of the defining characteristics of the HMLV industry is variability. Variability management is not often properly acknowledged when a lean implementation is considered in an organization (Zhou et al., 2016). Brikie and Trucco (2016) recognized that variability is often the barrier to successful lean implementation in the HMLV industry. However, demand variability does not affect the relationship between efficiency and lean, but has a negative impact on the relationship between responsiveness and lean (Bortoliini et al., 2019). Zhou et al. (2016) proposed that process variability, quality issues, machine breakdowns and setup times could be solved with Kaizen methods.

(20)

Buffers The impact of variability on manufacturing can be buffered with excess capacity, excess inventory or safety lead time (Hopp and Spearman,2000). The key element of the HMLV industry is the inherent variability in which buffers can have a significant role. Unfortunately, buffers are not comprehensively addressed in HMLV literature (Tomasevic et al.,2021). Inventory buffers are often found in the processes as WIP goods and lowering these WIP buffers often has a positive impact on the performance of the manufacturing processes (Tomasevic et al., 2021). Thurer (2014) claimed that a controlled order release,

as well as customer enquiry management, can be utilized to stabilize demand variability. Customer enquiry management will match the sales and the available capacity. This can effectively control the lead-time buffer through a due date function as well as the capacity buffer by planning the capacity over time (Thurer et al., 2014). This can prevent possible amplified overloading in the manufacturing processes and ensures that due dates can be met (Tomasevic et al., 2021).

Tomasevic et al., (2021) recognized that the literature regarding lean manufacturing in the HMLV industry lacks a deeper discussion of what might be considered to be waste. The definition of waste varies based on the author and has confused the definition of what is lean in the HMLV industry (Thurer et al.,2017). Some authors argue that the concept of waste needs to be adapted to different contexts (Tomasevic et al., 2021). The definition what is waste in LMHV and HMLV industries plays a significant role. For example, Bicheno and Holweg (2008) did not consider the excess capacity to be a waste in the LMHV industry, but for the HMLV industry, it is considered to be an asset, which maintains responsiveness and flexibility (Bicheno and Holweg,2008). Variability reduction is often done with a set of lean tools, but some variabilities are considered to be strategic variabilities, which are valued by customers. The strategic variability should be managed and not reduced (Deuse et al., 2013). Bortolini et al. (2019) noted that the reduction of strategic variability is often uplifted for making the process more efficient, which brings the HMLV environment closer to the LMHV environment. The reduction of strategic variability may have negative effect on competition in the HLMV industries (Thurer et al.,2014).

In the HMLV industry, the high amounts of WIP are often caused by deficient process controls, and not by the choice of buffering WIP. Manufacturers have two choices, lead time buffer or capacity buffer. Both of them have positive effects in the eyes if the customers, a lead time buffer shortens the customer’s waiting time and capacity buffer decreases the variability in production. Capacity adjustment strategies are often neglected in lean operations, which could play a role in variability buffering and help gain control of the processes. The last strategy, that remains unspoken in lean maturity, is swapping and buffer balancing. These two strategies help in achieving performance targets of operations. (Tomasevic et al., 2021)

The scope of lean in the HMLV industry is narrower compared to the LMHV industry. To master and succeed in lean, the differences between strategic and operational levels of lean need to be understood and absorbed (Hines et al.,2004).

The authors have noted that there is no discussion on the strategic level of lean

(21)

which is necessary to sustain lean in organizations. The small and medium-sized organizations in the HMLV industry can sustain the lean principles due to them being more operation-focused organizations compared to large organizations (Langstrand, 2009).

Internal supply chains are often large in HMLV organizations, due to the enormous product variety which often leads to different methods of production and overlapping manufacturing designs and activities (McGovern et al., 1999). Extending the lean principles to an entire supply chain is not considered in the HMLV articles. Further, assessing how waste in one stage affects later stages and how these stages contribute to value creation are not considered (Tomasevic et al., 2021). Extending lean principles to the external supply chain is difficult for HMLV industries, due to extending organizations usually having less negotiation power with the suppliers (Tomasevic et al., 2021). The negotiation power is lower due to HMLV manufacturers often being smaller organizations, which tend to be extremely reliant on their suppliers.

In addition to the inherent dependence on suppliers, the variability of products may require a large number of suppliers to be able to manufacture the products (White and Prybutok,2001). If an HMLV organization attempts to extend lean principles to their suppliers, they may encounter resistance from their suppliers. In the spirit of reducing and eliminating waste, HMLV organisations should strive to reduce the total number of their suppliers, which can often be dangerous due to the variability of products usually requires a large number of suppliers to be able to successfully manufacture all their products (Panizzolo, 1998).

Lean in the HMLV industry focuses on manufacturing operations, of which the central point is the shop floor. The main purpose of lean in the HMLV industry is to remove the obvious waste and use more advanced lean concepts. The advanced lean concepts are useful in the HMLV environment, but they are often abandoned. The scope of current research does not include other functions of the organizations and it is the topic for future research in the lean in HMLV environments, (Tomasevic et al., 2021).

2.2.2 Lean implementation, tools and practices in HMLV environment Generally, lean principles have been implemented into different organizations in the HMLV industry in two different ways: proposed frameworks and integration of lean with other approaches (Tomasevic et al., 2021).

Bhamu and Sangwan (2014) recognized that there is not any standardized lean implementation framework, which is a major topic in the research of lean in the HMLV industry. Without a durable and well-defined framework, the implementation success of lean is dependent on the common sense of the implementing manufacturer and their research, rather than justified and well-researched options (Karim and Arif-Uz-Zaman, 2013). Tomasevic et al., (2021) verified that there were 33 articles, which provided a framework for lean implementation in their study. 23 out of the 33 implementations were successful but the rest of the case studies were not successful.

The provided frameworks raised several issues, which were found in the literature.

The first issue is that there is no generalizability. The comparison of the proposed

(22)

frameworks was difficult due to frameworks including a wide variation of lean tools and practices, which can substantially variety from one another (Tomasevic et al., 2021). The second concern is that most of the frameworks are based on a specific lean tool, for example, VSM or Kanban (Tomasevic et al., 2021). The final major issue is that the HMLV environment is overly simplified and merged into the LMHV environment (Tomasevic et al., 2021).

Hines et al. (2004) proposed that lean implementation in the HMLV industry is most successful through integration with other approaches. Tomasevic et al., (2021) discovered that there were 22 articles that described the use of lean with other approaches. The approaches used in the literature were project management, CONWIP, Quick Response Manufacturing, Six Sigma, Theory of Constraints, Workload Control (WLC) and agile (Tomasevic et al., 2021). The most common way to integrate the approaches is performed by streamlining the manufacturing process using the alternatives of Kanban cards: POLCA, Drum-Buffer-Rope (DBR) and CONWIP (Roser, 2021; Tomasevic et al., 2021). Agile is used for improving flexibility and market responsiveness, and is also considered to be one of the lean practices by some experts (Papadopoulou and Özbayrak,2005). Even though only a few articles consider the combination of lean and agile, it still is under the research (Tomasevic et al., 2021). The rapid product variety from the start of the HMLV supply chain divides lean and agile operated parts in the supply chains (Tomasevic et al., 2021), which makes the integration of lean and agile research difficult. POLCA and DBR are valid options for organizing pull production in the HMLV industry, their advantages can be exceeded by the difficulty of managing the system in conditions with low routing variability or in a situation where the bottleneck shifts from one place to another (Tomasevic et al., 2021). WLC is the recommendation of Thrurer et al.

(2014) for achieving the most lean benefits in the HMLV industry, but the research for WLC in the HMLV industry has mostly been done with simulations and few practical implementations have been done to deduce reliably that WLC is the way to go within the HMLV industry (Silva et al.,2015).

Tools and practices

Shah and Ward (2003) conclude that there are four categories of consistent and logically correspondent bundles of lean tools and practices. The four categories and their practices are the following:

Just-in-time (JIT) The most commonly used tools are from the JIT bundle (Toma- sevic et al., 2021). The most used tools from this bundle are VSM, Kanban and cellular manufacturing technology. It is recognized that failure to meet the VSM assumptions, e.g., stable demand, fixed product routings and constant cycle times, are an issue in the analyzed articles in the HMLV literature review of (Tomasevic et al.,2021). The VSM issues can be overcome by the assumption that any graphical representation of process steps in the HMLV industry can be acknowledged as VSM (Forsman et al., 2011). Some other authors offer adaptations of VSM techniques to solve the VSM issues (Matt et al., 2014). Even with adaptations, some authors do not examine the complexities of the HMLV

(23)

industry by fixed cycle times and the existence of product families (Seth et al., 2017). For Kanban practices, there are different possible substitutions. These substitutions include job-specific Kanban, CONWIP, DBR, POLCA and WLC (Tomasevic et al.,2021). For the practices of cell manufacturing, some authors assume that there is an existence of product families and equipment dedicated to a certain product family (Hunter et al., 2004), which is not recognized by the other authors (Matt et al.,2014). It is discussed that the manufacturing layout should be in the form of manufacturing cells, which should simplify the manufacturing process (Tomasevic et al., 2021). Nevertheless, this kind of simplification is not possible or desirable in the HMLV environment and a functional layout is preferred due to it maintaining flexibility (Tomasevic et al., 2021).

Total Quality Management (TQM) The quality issues observed in the article (Tomasevic et al., 2021) were the inability to perfect the production process before the sale, switch quality requirements due to a large product mix, lack of opportunities to learn from mistakes and long lead times that prevent pausing the production when substandard quality products are found in the production processes. Birkie and Trucco (2016) proposed continuous improvement programs as standard lean practices, but the successful outcome of this proposition is not reliable. Establishing a continuous improvement system is difficult if the standardization of the quality is not attained (Deflorin and Scherrer-Rathje, 2012).

Total Productive Maintenance (TPM) TPM is acknowledged as a normal practice in lean manufacturing and it is not routinely discussed in the HMLV context (Tomasevic et al., 2021).

Human resources Management The HMLV industry needs to achieve higher standards in motivation and enthusiasm of employees, housekeeping, quality assurance, preventive maintenance and machine repair (Hendry,1998). These issues can be found in every corner of the HMLV industry, if there is pride in the workplace, the readiness and motivation to improve are much higher.

Having a workforce which works in a cross-functional manner is a standard lean practice (Shah and Ward,2003), but in the context of HMLV, it may not be the best solution as it may be expensive to train the workforce and the learned skills may never be used (Tomasevic et al., 2021).

Some lean tools are suitable for the HMLV industry as such, while some tools are difficult to implement without adaptations (Tomasevic et al., 2021). There are no universal HMLV lean tools, which is partially due to the lack of relevant research (Tomasevic et al., 2021). Lean tools are applied and used without a full understanding, which is required to define the rules that determine the behaviour of the system (Lander and Liker, 2007). Some JIT practices that are suitable for the HMLV industry continue to be unknown to this date (Tomasevic et al., 2021). The practical applicability of TPM is high in the HMLV environment, but the maintenance

(24)

issues prevalent to TPM are often not properly addressed. This is understandable due to equipment effectiveness is not prioritized in the HMLV industry (Tomasevic et al.,2021).

2.3 Manufacturing control

ERP is defined as a system for effective planning and controlling of all the resources needed to take, make, ship and account for customer orders in distribution, manufacturing and service organization (Madanhire and Mbohwa,2016). This integration with different functions is possible with software package solutions offered by vendors, which support the integration of financial, accounting, human resources, supply chain and customer information through the company (O’Leary, 2000). Traditional manufacturing has treated each of these transactions between functions separately and ERP sends treating these transactions separately and enables cross-function information flow (O’Leary, 2000).

2.3.1 ERP modules

In the implementation of ERP systems, it is assumed that the organizations may have multiple operation and control locations. Therefore, the online data transfer is done across locations (e.g., Intranet, Data warehousing and Workflow) to facil- itate transactions. This is the reason why an ERP system is made from different modules that are selected based on the economic and technical feasibility of given manufacturing units (Madanhire and Mbohwa, 2016).

The most included modules for organizations are:

ERP production planning module This module optimizes the usage of manufacturing capacity, components, parts and material resources based on the forecast of sales and historical production (Madanhire and Mbohwa, 2016).

ERP purchasing module Acquiring raw materials can be heavy work and the ERP purchasing module helps the process. The module automatically identifies potential suppliers, negotiates prices, places orders to suppliers and bills the suppliers (Madanhire and Mbohwa, 2016).

ERP inventory control module Keeping track of the item levels of warehouses can be done with the ERP inventory control module. It maintains appropriate levels of stock in the warehouse by identifying inventory requirements, setting targets, providing replenishment techniques and options, reconciling inventory balances, monitoring usage and reporting inventory statuses (Madanhire and Mbohwa, 2016).

ERP sales module It contains order placement, order scheduling, shipping and invoicing, which are crucial for every organization (Madanhire and Mbohwa, 2016).

ERP marketing module It provides direct mailing campaigns, trends in customer tastes and lead generations (Madanhire and Mbohwa, 2016).

(25)

ERP financial module One of the core modules of the ERP system is the ERP financial module. It collects all the financial data from various departments and generates reports. These reports are balance sheets, general ledger, trial balances and quarterly financial statements (Madanhire and Mbohwa, 2016).

ERP human resources module This module maintains a complete employee database (e.g. contact information, salaries and performance evaluations) (Madanhire and Mbohwa, 2016).

To fully make use of an ERP system, Business Process Re-engineering (BPR) needs to be exercised. BPR is a reconsideration and total redesign of the organizational process to achieve radical improvement of current performance in speed, service and cost (Sumner, 2000). BPR cannot be exercised properly if the ERP has not been implemented, ERP is there to consolidate the process adjustments and rejuvenation (Madanhire and Mbohwa, 2016).

The standard flow chart of ERP involves top management, operations management, basic computer data and execution of plans. The top management is in charge of coming up with objectives, which will be linked to the sales planning and further down the sales planning is linked to production planning. Operation management planning will be responsible for master scheduling according to production planning, which then leads to material planning and capacity planning. To schedule and plan accurately, basic computer data is used for validating schedules and plans. If the plans are accepted, the execution of the plans will take place. Operation management are in charge of purchasing material, shop scheduling and measuring the performance, (Madanhire and Mbohwa, 2016).

The implementation of ERP will need changes in the staff and practices (Gefen and Ragowsky, 2005). The most cost-effective way of implementing ERP systems is with external consultants who are specifically trained in ERP implementation. The consultants are responsible for the initial stages, training employees, customising interfaces, troubleshooting and workflow study. The most commonly used operation measures in ERP are capacity levels, utilization and efficiency, (Madanhire and Mbohwa, 2016).

Resistance

The implementation of ERP systems leads to methodological and fundamental changes in the company. These changes will influence the opinions of employees on the ERP systems in use within the organizations, and will divide them into two different groups: opponents of the systems and supporters of the system. The main causes, for employees who are opposing the system, are retraining to acquire new professional knowledge and skills, the possible change of profession, changes in the paycheck, changes in the motivation to work and fear of losing your job (Klopova et al., 2018). The management of the company is responsible for achieving staff commitment to changes and reducing staff resistance to the changes (Svistunov et al., 2020).

(26)

To reduce negative reactions of employees, effective methods of resistance management need to be used carefully. When resistance management takes place, it is expected that resistance will respond to the resistance management. The resistance in ERP system projects can be seen as passive participation of employees, refusal to participate in ongoing training programs or the retraining of the profession, the use of hidden tactics of disagreement and hidden sabotage regarding the changes. The causes and reasons for resistance, possible consequences and staff category can be found in the table1 (Svistunov et al.,2020).

Reason for occurrence

Reason for resistance

Possible consequences

Staff category Mistaking the

main target of ERP systems and lack of basis for achieving targets

Low level of understanding of the basic principles, tools and capabilities of ERP systems

Slowdown, passive involvement in the implementation or hidden sabotage

Low-level managers, specialists

Mismatching with the declared opportunities of ERP systems

Increase in labour productivity

Decrease in the motivation

Middle managers, specialists

Not considering company specifics during the implementation

Implementation of unitary solutions that convolute the management processes

Lower efficiency of management processes

Low-level managers, specialists

Not motivating staff during the implementation

Lack of motivation to be involved in the implementation of ERP systems

Slowdown or passive involvement in the implementation

Middle and low- level managers, specialists, workers

Mistaking the project target and personal targets of employees

Terrors in changing working conditions and payments

Slowdown of personal involvement

Low-level managers, specialists, workers

Table 1: The reasons for occurrence, resistance, possible consequences and staff categories of staff in the implementation of ERP systems, (Svistunov et al., 2020).

To prevent resistance, trust between management and employees should be increased. Also developing effective motivations aiming at the creation of necessary conditions for the attentive involvement of staff is of paramount importance. Fur- thermore, employees need to be convinced of the fact that the system is a necessity and inevitable. Lastly, increasing the staff awareness of the targets, objectives and progress of the ERP system supports the prevention of resistance, (Svistunov et al., 2020).

(27)

2.3.2 Benefits

ERP systems have positive effects on the organizational subunits and these subunits must often change to fit the ERP system (Gattiker and Goodhue, 2002). The ERP system can gather, receive, analyze and store information about the markets, as well as develop and support big data storage, which can be utilized for numerous algorithms (Svistunov et al., 2020). The right information can be found quickly by well-trained employees (Svistunov et al., 2020). The implementation of the ERP system enables improvements in the operational efficiency of the data captured by the system (Madanhire and Mbohwa, 2016). The visual ERP tool developed by Thron (2008) improves the planning capability, delivery performance, product flow, schedule adherence and self-directed teams autonomy.

2.3.3 Production planning and control

Production planning, the heart of the operations, is the process of planning and allocating raw materials, people and workspaces to manufacture the products on time (Biswas and Baral, 2021). In the current highly competitive industrial environment, increasing customer demands and expectations need to be fulfilled by production planning and control. ATO tasks are scheduled by the production planning when the customer payments are placed. Also, MTS work orders are placed in a timely manner by the production planning (Biswas and Baral, 2021). The objectives of production planning and control are to reduce WIP, Shop Floor Throughput Times, leading times, stock retaining costs, improve on responding to demand variations and improve on delivery date adherences (Biswas and Baral,2021). These a crucial objectives, which suggest that having the best PPC system is a strategic choice (Esperet and Piolat, 1991). In the manufacturing cycle, PPC focuses on what should be produced, the time and date when it should be produced and the quantity that should be produced. To maximize the manufacturing cycle, a longtime view of the preparation of production is required to produce the optimal outcomes, (Biswas and Baral, 2021).

PPC responsibilities

The PPC process starts by identifying a demand for a product, which will lead to a creation of a production plan that will meet the demand. Production planning is a way to organize a set of operations so that the producers are in the right places at the right time, which will maximize the available resources. PPC is divided into two different categories: production planning and production control, in which both of which have their phases (Biswas and Baral, 2021).

Phases included in the production planning are:

Planning The planning phase obtains information from the sales section regarding the amount to be produced and the promised delivery dates. The engineering section is also providing information on what should be promised but with engineering and drawing specifications. This allows the planning section to produce planning activities (Biswas and Baral, 2021).

(28)

Routing The direction of the work and the sequence are decided by routing. The purpose of routing is to find the most efficient and cost-effective sequence of instances (Biswas and Baral, 2021).

Schedule The process of estimating the time for completion and operation, and the time required to finish the entire series is known as scheduling. Scheduling requires the creation of a timetable that includes the required time to create the product, time spent on each piece of equipment and the procedure (Biswas and Baral, 2021).

Loading The amount of work is considered to be a load, and assigning jobs to work centres or equipment within work centres is called loading (Biswas and Baral, 2021).

Phases included in the production control are:

Dispatching Transferring something to a specified location (Biswas and Baral, 2021).

Following Up This phase analyzes whether the work is progressing as planned and how significant the deviations from norms are. It also takes corrective measures to restore law and order (Biswas and Baral, 2021).

Inspection This phase includes the same measures as the following up phase but in addition the inspection phase assesses how the work has been completed as well as deviations from the norm (Biswas and Baral,2021).

Corrective Routings, jobs and the talks with workers are all part of this (Biswas and Baral, 2021).

The main factors that affect PPC are the form of products and the type of manufacturing. In PPC, the complexity of the product is the most important aspect to assess for the form of the product. In the production control sector, the type of manufacturing is a more significant element (Biswas and Baral, 2021).

PPC is an interactive function and has interrelations with most of the sectors in the manufacturing process, which hints that PPC is widespread and important.

PPC have five different roles in operations management, which are attaining and catalogue management, industrial and assemblage, marketplace prediction, engineering stipulations and quality control (Biswas and Baral, 2021).

Attaining and catalogue management includes tasks for scheduling the timely purchase of fresh materials, machinery and replacement portions. Also, other tasks related to materials involve purchasing, inventory control, storing, diversity decrease and examination. Industrial and assemblage include organization and production planning in general. Marketplace prediction forecasts future demand patterns for manufacturing goods, which is useful information for production planning and management for sketching future work shifts and plans to increase or decrease manufacturing or expand the manufacturing plant. Engineering stipulations will provide new directions for the shop floor for engineering customized products, for

(29)

PPC, they need to gather important data for shop orders and change routing times, to complete the customized product. PPC need to guarantee that quality standards are followed, which results in quality control. In a highly dynamic and changing industrial environment, having good quality control ensures that customers will receive high-quality products, (Biswas and Baral, 2021).

Multi-factory production planning

The manufacturing industry has moved from single-factory production to multi- factory production due to geographically dispersed factories that may save costs and potentially increase efficiency while being under constraints of varying capabilities and restrictions. In a multi-factory environment, PPC needs to assign orders to potential factories beforehand. The major drivers to increase efficiency in the network and utilize the potential are strategic decision making, production planning and scheduling. For multi-factory optimization Pinedo (2014) has done a scheduling optimization with multiple objectives according to assigned orders, specific periods, customer demands and forecasts. Multi-factory PPC is also known as distributed PPC, which is built upon coordination, collaboration and synchronization between factories (Lohmer and Lasch,2021).

In a multi-factory setting, the five most used job configurations are open shop, job shop, flow shop, parallel machine and single machine. In the open shop configuration, there are no job order constraints on operations. In the job shop, the job orders are determined according to the product. In the flow shop, every job has the same job order. The job configuration needs to be considered in the production planning for increasing efficiency. The network structure and the configuration of the underlying supply chain or production network differ for each organization. In parallel structure, the factories compete for the orders on the same level and the operation for the job takes most likely in the available factory. In serial production, the production takes place in several stages and several factories. The serial line can be split up into different factories which do not produce the same goods, e.g factory produces sub-assembly parts for three different factories (Lohmer and Lasch, 2021).

Multi-factory settings present characteristics which makes them more complex than single-factory setting. The first characteristic is transportation. The costs of transporting the raw materials, between factories need to be considered, as well as the possible transportation in the factory. The transportation influences the lead time and if there are any inventories in between them, then the product lead time can increase drastically. The second characteristic is the presence of stochastic parameters.

Multi-factory scheduling, transportation, machine breakdowns and the work culture will increase the stochasticity of the final lead time. The last characteristic is the problem of how one benchmarks different job configurations. Currently, there are no benchmark instances for different job configurations in a real-world multi-factory setting (Lohmer and Lasch,2021).

Different types of solution methods have been used in the scheduling of products in a multi-factory environment. These are meta-heuristics, integer programming models, heuristics, simulation, exact solution methods, non-linear programming,