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bstract

What effect has the implementation of Automation Technologies had on factory based

employment in the United Kingdom: A Case Study.

This study was designed to examine the effects automation technologies have on

factory based employment in the United Kingdom, utilising an international market

leading food production case study. Cerestar UK, based in the North West of England

manufactures starch derived Caramel Product in its new, recently automated Caramel

Facility. The rationale of the study was formed from the common belief that such

automation technologies are responsible for widespread migration patterns from

industry to service sector employment.

Comprehensive interviews with Cerestar UK’s Caramel Factory Manager and Aston

Dane PLC’s Automation Project Manager were conducted. Alongside this mixed style

questionnaires were circulated to subjects at the very heart of this change, Cerestar

UK’s Caramel Plant machine operators. All subjects were asked how and why they feel

such technologies were implemented, focussing on any positive or negative effects

which have arisen from this.

All collected data was then analysed using quantitative and qualitative methods, and

compared with a comprehensive literature review in an attempt to gain a better

understanding of the relationship between automation technologies and employment.



Contents

Chapter One: Introduction – Page 1

• The forming of the research rationale.

• Background and Context to the Study.

Chapter Two: Research Methods – Page 3

• Detailed description of Research Methodology.

•

Justification for such Methodology.• Description of Data Analysis Methodology.

Chapter Three: Literature Review – Page 7

• “The body of written work produced by scholars or researchers in a given field”

(yourDictionary, 2003)

•

Includes Automation Types Diagram – Page 14

Chapter Four: Cerestar UK – Page 15

• About Cerestar UK and its new Trafford Park based Caramel Plant.

• About the role of Aston Dane PLC.

Chapter Five: Discussion – Page 19

• Analysed Research Data.

• Comparisons with Literature Review.

• Explanations and Interpretations.

• Includes Automation Types Diagram – Page 26



Chapter Six: Conclusions – Page 27

• Summary of research outcomes.

• Brief Research Evaluation.

Research References – Page 30

Research Log



Chapter One: Introduction

Research: “creative work undertaken on a systematic basis in order to increase the

stock of knowledge, including knowledge of man, culture, and society and use of this

stock of knowledge to devise new applications” (Frascati, 1993).

“Automation: Any continuous and integrated operation of a production system that uses

electronic or other equipment to regulate and coordinate the quantity and quality of

production” (Buckingham, 1961, p6). Benson et al (1983) writes “Factory labour

gradually evolved into the dominant method of production during the nineteenth

century”. However, “The shift to service employment can hardly be denied. For

example, in Britain, employment in services has grown from 53 per cent of total

employment in 1971, to 73 per cent in 1993 (Employment Gazette 1994)” (Compton et

al, 1996). Heathcote (2000, p2) states, “In the 1980s, thousands of factory workers

were made redundant by the introduction of robots on the factory floor making

everything from biscuits to cars… today, most people no longer work in farms or

factories but are found instead in sales, education, health care, banks, insurance firms

and law firms… knowledge and information work account for about 70% of the labour

force in Britain”. Many commentators argue the reasons for these migrations in

employment, Benson et al (1983) feel such debates have raged since the 1950s, dividing

those concerned into two distinct categories, technological determinists, “Automation

helps the promise of a future of new abundance, new leisure and new freedoms (Walter

Reuthers, President of the United Automobile Workers Union, Speech, 1955)” (Faunce

1968), and technological non-determinists, “this machine evolution leads to the very

situation feared: Automaticity grows until no operations are required: then what



employment opportunities exist in the factory? Only maintenance, set up, and design”

(Kaplinsky, 1984, p134). Furthermore, Bright (1958, p188) argues even these activities

have become victims to automations pervasiveness. However, whatever the reasons it

cannot be ignored that Britain during the latter quarter of the twentieth century

underwent a process of deindustrialisation.

Matzner et al (1991, p3) feels there is however one certainty, “the rapid diffusion of

new technology exerts a strong impact on employment trends”. It is these effects upon

employment trends that formed the rationale for this research piece, utilising a case

study focussing on a modern day implementation of automation technologies. Cerestar

UK, based in Trafford Park, Manchester, is an international market leader of starch

derived Caramel product, having recently undertaken outside consultancy provided by

Aston Dane PLC to build a new, mostly automated Caramel Plant division, ultimately

decommissioning the older manually operated plant. The initial aims of the Caramel

Project were to “provide a plant with a high level of automation using site standard

technology whilst integrating the new plant into existing network infrastructures”

(Aston Dane PLC, 2002).

Alongside the case study a comprehensive literature review has also been conducted.

This will assist in providing structure, focus, factuality and relativity to the

aforementioned case study, examining and clarifying if such processes of thought

remain valid and appropriate to a modern day implementation.



Chapter Two: Research Methods

Methods: “A means or manner of procedure, especially a regular and systematic way

of accomplishing something” (yourDictionary, 2003).

After forming the rationale for this study, it became apparent that like all research

pieces a great deal of literature reviewing was required, Verma et al (1981, p10) states

that literature reviews help researchers “identify and explain relevant relationships

between the facts… the researcher must produce a concept or build a theoretical

structure that can explain facts and the relationships between them”. Without referring

to literature, it would be impossible to accurately draw comparisons, make predictions,

support or refute arguments and ultimately evaluate research pieces.

However, whilst conducting the literature review, there were issues to be aware of,

Katzer et al (1998, p5), suggests “not all researchers or editors are equally

knowledgeable or competent… Many people, however, would underestimate the

seriousness of the errors, assuming that small mistakes may be the problem”. Such

literature problems stem from authors lack of background knowledge, poor research

practices, miscalculations or even outright bias. The extent of such problems are

highlighted further, “in a study of the quality of educational research, expert researchers

evaluated a random sample of 81 articles… they judged that only 7 percent of the

articles were worthy of publication” (Katzer et al, 1998, p5). Each article was therefore

judged according to its own individual merits.



To compliment the literature review, it was the aim of this exercise to utilise an

appropriate case study of Cerestar UK’s Caramel division. This was done by

questioning those employees directly affected by such implementations, utilising a

mixed style of open and close ended questions, also conducting a short interview with

the floor manager responsible for overseeing such changeovers, Kevin Oliver. An

interview was also conducted with Shane Pugh, the project manager on behalf of Aston

Dane PLC, the consultancy firm responsible for implementing the new Caramel Plant.

To extract appropriate data for the study alongside the literature review, the use of

questionnaires were employed because Bell (1993), feels these can be simple and

effective if utilised correctly, also containing the added bonus of “collecting certain

types of information quickly and relatively cheaply” (Bell, 1993, p76). However Bell

considers their usability to only be apparent after preliminary planning and consulting,

therefore the scope for such methods was not finalised until the appropriate stages were

complete. Bell also feels that it is extremely difficult to design a suitable questionnaire,

suggesting many ‘golden rules’ of effectiveness. Questionnaires by their very nature are

also plagued by generally low response rates.

Interviews were also used, these are considered to be much more flexible to particular

situations and yield higher response rates than questionnaires. As Bell (1993, p91)

writes, “A skilful interviewer can follow up ideas, probe responses and investigate

motives and feelings, which the questionnaire can never do”. Simple factors such as

body language can initiate responses sometimes concealed through questionnaires;

however many argue subjects can feel much less pressurised when completing a

questionnaire alone as opposed to the interpersonal nature of interviews. Despite the



much greater depth and validity of an interview, they are considered to be extremely

time consuming, more prone to biases and often require a high level of experience from

the interviewer.

Because each method of research contains positive and negative aspects, both

questionnaires and interviews were used. The interviews themselves were only

conducted to two people, and were kept to an appropriate time limit to comply with

constraints of the research piece. The questionnaires however were distributed to 24

employees within the Caramel Plant; this proved a much more efficient way of

surveying a slightly larger sample.

An alternative to both questionnaires and interviews considered was that of focus

groups, “a group comprised of individuals with certain characteristics who focus

discussions on a given topic of issue” (Anderson, 1990, p13). Focus groups were

traditionally a market research tool and are considered by Morgan (1993) to be useful in

seeking opinions of groups with limited power and influence; however a major

drawback to focus groups is that participants should ideally be unknown to each other,

therefore making an organisational study somewhat impractical.

“Data collected by means of questionnaires, interviews, dairies or any other method

means very little until they are analysed and evaluated” (Bell, 1993, p125). When

analysing data collected from questionnaires, there were different types of questions to

be considered, list questions, allowing for multiple responses, category questions,

requiring single answers, grid questions, asking multiple questions and scale questions,

initiating responses on the basis of feelings and attitudes. There were also two basic



data collection methods to be considered, a mathematical quantitative approach,

“quantitative researchers collect facts and study the relationship of one set of facts to

another” (Bell, 1993, p5), and qualitative approach, “understanding individuals

perceptions of the world” (Bell, 1993, p6). However, when initially designing the

research questionnaires it became apparent that a mixed approach was required to

obtain the necessary data for this research. Because only a small sample of interviews

were conducted, this only allowed for the collection of appropriate qualitative data.



Chapter Three: Literature Review

Literature: “The body of written work produced by scholars or researchers in a given

field” (yourDictionary, 2003).

Automation was originally given formal recognition by the Ford Motor Company in

1946, “using it to describe automatic work feeding and material handling devices”

(Bright, 1958, p4-5). Automation is considered to be after mechanisation and assembly

lines, “the third phase in the development of technology that began with the industrial

revolution of the eighteenth century” (Buckingham, 1961, p4). Disputing this, business

philosopher Peter Drucker writes “Automation is not gadgeteering, it is not even

engineering! It is a concept of structure and order of economic life, the design of its

basic patterns integrated into a harmonious, balanced, and organic whole”

(Buckingham, 1961, p6).

Kaplinsky, (1984, p24-26) writes there are however different types of Automation

based within three spheres of design, manufacture and coordination. These are Intra-

Activity automation, Intra-Sphere automation and Inter-Sphere automation, see figure

1. Intra-Activity automation or ‘Island Automation’ refers to single process based

solutions separated from other processes of production. Kaplinsky states that this may

range from simple substitution of human power to complex artificial intelligence. Inter-

Sphere automation refers to linked processes within the same spheres; this type is

considered to be the beginning of organisational factors differentiating automation over

mechanisation. Inter-Sphere automation is the most complete form of automation,

involving synchronised coordination of all three spheres to ensure the technologies



work in harmony, “in this case automation technology links up different activities

between different spheres of production” (Kaplinsky, 1984, p26).

Whichever type, automations effects cannot be ignored, “The number of white-collar

workers is increasing, and at the same time the number of blue-collar workers is

decreasing” (Marcson, 1970, p4). The Employment Gazette 1994 writes, “The shift to

service employment can hardly be denied. For example, in Britain, employment in

services has grown from 53 per cent of total employment in 1971, to 73 per cent in

1993” (Compton et al, 1996). Heathcote (2000, p3) states “the introduction of

technology has in many instances led to a change in types of job available”, citing the

introduction of robotic assembly line technology as a major factor. Purnell (2000)

writes, “Many business reasons are cited for the introduction of robotics including

improved product quality and reductions in unit production costs. For the food industry

the benefits of robotic automation are improved quality, in terms of hygiene and

repeatability of processing, and reduced labour costs”, something which Gray (2001)

further emphasises, “The drivers for automation in the food industry include:

consistency of product quality, supply chain integration, hygienic operation, human

factors, legislation and economics”.

It is these proposed advantages which led a huge take up of self-regulating automation

technologies in post war Britain. Bright (1958, p83-84) lists such organisation

advantages of automation technologies to include cost reductions, operational

improvements, working environment improvements, product advantages, survival

advantages and business pride. “Reduction in required floor supervisors, inspectors, and

support personnel, such as payroll, personnel, food handling and health personnel, can



be substantial” (Riley, 1983, p8). However, cost reductions where concerned with

labour downsizing have long been a major argument against automation technologies,

Faunce (1968) believed such implementations should be government controlled to

prevent large scale labour displacement. Jackson (1998) refers to a common Marxist

thesis: Such technologies will create “a massive reserve army of the unemployed while

concentrating wealth, power and industry in the hands of the capitalist few”,

discrediting this he writes “The English textile industry is another graphic example that

should have caused mass unemployment. A variety of inventions and innovations led to

a massive rise in productivity. It was estimated that by 1812 the productivity of a

spinner was 2000 percent greater than in 1770. So great were the increases in

productivity by the 1800s that some workers, fearing technological unemployment,

resorted to machine-breaking, even though the expansion of employment in the industry

had been spectacular”. Kaplinsky (1984, p7) also refutes automations link with

unemployment “It is perhaps worth noting that in drawing this particular link between

automation and crisis we are going against the conventional wisdom which has tended

to argue that the crisis in Western economies has arisen because of the diffusion of

labour-saving automation technologies. In contrast, we have suggested… that the crisis

emerged first, for largely autonomous reasons”. This is not to say that technologies, like

automation do not effect employment, “David Ricardo noted in 1821 that technical

change is a two-edged sword-it can both destroy and create jobs” (Freeman and Soete,

1987). The 1994 OECD Jobs Study concluded that “Technology both eliminates and

creates jobs, generally it destroys lower wage, lower productivity jobs, while it creates

jobs that are more productive, high-skill and better paid” (South Western College,

2002).



It is this ‘upgrading’ of employee requirements which prompts further argument.

Manufacturers, managers and enthusiasts all believe that automated labour saving

technologies rekindle humanity into monotonous, inhumane work, whereas many

labour leaders and trade unionists adopt Dr. Norbert Weiner’s approach believing

higher skill requirements alienate ordinary labour, “the automated plant becomes a

technological lockout of the common man. Such a factory will need superskilled

specialists, not ordinary labour” (Bright, 1958, p176). Alienation of a particular labour

group is not necessarily contributory to spiralling unemployment, “if additional skills

are required of the workforce, there is always the possibility that existing groups of

workers will be displaced by newcomers” (Matzner et al, 1991, p13), it simply

demonstrates David Ricardo’s two edged sword theorem, emphasising that old jobs

may not be instantly replaced in terms of skill or location.

However, “nearly all forms of technology have enormous potential for human

betterment but, if not clearly understood, can do more harm than good, this is especially

true of automation… Even to the sceptic, automation offers the opportunity for greater

output, shorter working hours… safer working conditions… standardised quality and

more efficiency” (Buckingham, 1961, p2-4). Whilst many are quick to point out

negative effects of automation, very few commentators realise potential benefits of such

implementations, “An obvious and logical conclusion… is a reduction in the working

week to enable more people to be employed and in such a way that more time would be

available for leisure” (Kaplinsky, 1984, p147), however without appropriate pay

restructuring or uniform international agreement such reductions and accommodations

could severely inhibit economic competitiveness.



Although many claim an overriding factor of automation is ultimate cost reductions,

“automatic assembly becomes more attractive in terms of direct labour cost reduction”

(Riley, 1983, p3), Bright (1958, p83) disputes this, “Perhaps the most widespread

statement in automation literature is that the principle objective for automation is to

reduce labour cost. Yet this is only a half-truth. Underlying most of these situations

(Ford, Growmore, Elkhart…) was primarily the need for more capacity”. Bright (1958,

p170) further writes that productivity and capacity gains are variable to a number of

factors, the scale of automations advance, the industrial genre, changes in work content

and the overall volume of operations required. Automation technologies themselves

bring about such productivity gains through advancements in speed, capacity,

compounding, additional mechanisation and the mechanisation of control. Kaplinsky

(1984, p114) refers to a particular rule of thumb, “the so called ‘0.6 rule’ which states

that the increase in costs of equipment is generally in the same ratio (i.e. 0.6) to the

increase in capacity”.

But does this increased production come at a cost to the worker? “In the pre-industrial

periods both skilled craftsman and peasants had considerable control over the rhythms

and movements of work. But the machine system now controls the pace of work and

restricts the employee’s free movements” (Marcson, 1970, p13). Levidow et al (1981)

also writes, “Capitals priority for automation is to attack those stages of the productive

cycle which have the most space for workers to hold their own pace of work”. Such

losses of control have simply threatened to turn workers into mere powerless

instruments; it was Karl Marx who originally advanced the theory of the alienated

human relation to industry, human intelligence being substituted for machine

intelligence. A study by Noble (1976) revealed how numerical control machinery had



indeed made traditionally skilled workers slaves to the machine, whilst further studies

by Shaiken (1981) reinforced employee alienation, “I’ve worked in this trade for

seventeen years. The knowledge is still in my head, the skill is still in my hands, but

there is no use for either one now. I go home and I feel frustrated, like I haven’t done

anything” (Kaplinsky, 1984, p135). Bright (1958, p187) writes there is a logical theory

on employee-machine relationships, as automaticity increases the demands on users rise

and fall, initially mechanisation relieves manual effort, increasing control, but as fixed

control and automatic measurements are implemented the machine gains artificial

intelligence, restricting the users overall control. Marcson (1970, p13) writes that such

technologies have enforced responsibility, problem solving and decision making to

supervisors and away from core staff. However, Faunce (1968) concludes that

automation does not increase job specialisation and alienation, but that it promotes a

sense of ‘job-enlargement’ and responsibility. Lindenfeld (1973, p239) writes that

employees may not consciously experience job alienation, however if they do

“employees may tolerate it because they get higher pay, pleasant working conditions

and fringe benefits”. Lindenfeld also writes that the increased centralisation automation

brings is not necessarily beneficial to the employee, “Work can be more satisfying if

large factories are decentralised into smaller units” stating that decisions made in lower

hierarchies are simply to achieve predetermined ends, further promoting employee

powerlessness.

Marcson (1970, p2-3) writes “automation has introduced new principles of control and

decision-making in which the human is eliminated as operator and instead functions as

supervisor”, this is further validated by Faunce (1968) who feels automation

technologies simply “degradate jobs to the role of a button pusher”, for example a



factory assembler would require different skills to that of robot operator/controller,

therefore increasing the chances of such labour displacement theories proposed by

Marx. Purnell (2000) cites robotic meat cutting as an example of automations

effectivity, “Previous work at Bristol (university) has shown that a robot can cut more

accurately than a human”.

Therefore if factory assemblers now require different skills in modern factory

environments, retraining must become a central issue of change. Marstrand (1984, p18)

writes “in a time marked by rapid technological change… it is not easy for people over

fifty to readjust”. However, Bright’s (1958, p125) own research leads him to conclude

“Contrary to much speculation, the training of the operating workforce is not a

problem”, referring to thirteen case studies investigated.



The Three Different Types of Automation (Kaplinsky, 1984, p27)

Design Coordination

Manufacture

Automation

(a) Intra-Activity

Automation

Automation

Design Coordination

Manufacture

Automation

(b) Intra-Sphere

Automation

Automation

Design Coordination

Manufacture

(c) Inter-Sphere

Key

Activities

Spheres

Automationtechnologies



Chapter Four: Cerestar UK

Case Study: “A detailed intensive study of a unit, such as a corporation or corporate

division, that stresses factors contributing to its success or failure” (yourDictionary,

2003)

Cerestar UK a leading international food production company originally produced

starch derived Caramel product in their old, now decommissioned plant; this was

approximately thirty-thirty five years old. A factory of this age was considered to have

major health and safety issues, not least to its workforce but also to its ultimate

consumers. Food production requires exceptionally high hygiene standards; therefore it

was determined the Caramel Plant was potentially a liability. This was further

exacerbated by the pressure Cerestar experienced from its major international clients, as

the prospect of losing such orders could financially cripple the company.

Because of this Cerestar looked to invest in a completely new Caramel Production

facility rather than merely upgrading the old plant. It was at this point that automation

process engineers, Aston Dane PLC, accompanied by Ventron, specialists in chemical

process design, procurement and contract management became involved. The two

companies had previously collaborated on other Cerestar projects, so the basis was

already cemented for involving the two in the new Caramel Plant. The new plant,

although initially to remain competitive in today’s “automate or liquidate” society

(McLoughlin et al, 1988), also boasted a range of advantageous features, for example a

more pleasant working environment, safer, more efficient and more hygienic. However



projects like this are often “purely to maintain business” (Shane Pugh, 2002) rather than

other such issues.

Before the project itself began huge amounts of planning were involved, firstly Aston

Dane and Ventron engineers sat down with Cerestar’s management to establish a need

and profile for the new plant. Only after these series of meetings and the building of a

comprehensive knowledge could engineers begin to draft ‘Process Engineering Line

Diagrams’, identifying where and how the facility should be constructed. Aston Dane

PLC remained involved and responsible for the project right throughout its design

procurement to live process commissioning.

The whole process from its initial procurement to production took approximately

twenty six months, with the first meeting being held in December 1997 and the project

close-out meeting being in February 2000, well within the scheduled time limit for the

project. Initially the project was estimated at £10 million; however Cerestar’s European

board turned this down, compromising at £7 million, with a further £0.5 million

generated from site revenue.

The original estimate of £10 million was to fully automate the plant, with every valve

actuated, however the main casualty of such cost reductions was downsizing the scope

of automation, to approximately 75% of the whole process, also reducing the amount of

reaction vessels installed from five to four. The main valves are however automated,

with the less frequently required valves remaining manual, but utilising feedback

sensors prompting the operators when actuation is necessary. Route Selection was also



a casualty of cost cutting, requiring the manual configuration of valves to ensure the

right materials are fused together in the correct pans.

Due to infinite variations product sampling itself can never be automated in such

conditions; however when a sample is due the computer prompts the operator to take a

manual sample, which is then analysed in the facilities laboratory. The analysed results

are then fed back through the computer which in response adjusts appropriate variables

to ensure the batch comes out within the specified code. This is in stark contrast to the

manual based system which required the operators to judge when samples are taken, a

knowledge only really gained through experience. It is argued that this allows a more

consistent, better quality final product, eliminating the scope for human error. However,

some commentators question the validity of such claims, “Automation is a tool

available to high-volume manufacturers to reduce two major expense areas, product

assembly and product quality” (Riley, 1983, p61).

A major advantage of these automation technologies was therefore the increased

efficiency they promote throughout the production process and also in terms of their

labour force. Through natural wastage Cerestar reduced the need for temporary

workers, allowing for a slight downsizing within the workforce.

Moving from manually based systems to automated would obviously drastically change

the appearance and operations of the Caramel production process, the most obvious

change would be the appearance of computer screens and a central console from which

the whole plant can be operated. This console room itself is shut off from the main plant

section and is without windows, using CCTV cameras to monitor the pans, purely for



safety reasons associated with glass within factory conditions. It is this use of

computers over the traditional manual production methods that interest many writers,

“new machinery requires new skills of labour and new knowledge and abilities of

management” (Buckingham, 1961, p8). Other writers however feel this shift in terms of

skill has not only promoted more humane work, but created jobs that are “more

productive, higher-skill and better paid” (OECD Jobs Study, 1994).

The Caramel project as a whole was deemed to have been a great success, receiving

glowing praise from Cerestar’s own in house project reviewer Alan Moore, stating it

was his “most successful automation project in twenty eight years” having been

completed on time and well within the allocated budget. Aston Dane themselves feel

proud to have been the ‘filling’ in the sandwich between what the management wanted,

and what the operators required.



Chapter Five: Discussion

Discussion: “The consideration of a topic” (yourDictionary, 2003)

“Automation is not gadgeteering, it is not even engineering! It is a concept of structure

and order of economic life, the design of its basic patterns integrated into a harmonious,

balanced, and organic whole” (Buckingham, 1961, p6). Shane Pugh (2002) also feels

automation is not simply about the mechanisation of equipment, but also of the

automation of processes through many different levels, ranging from single process

automation to global factory automation. Kaplinsky (1984, p24-26) distinguishes three

such categories, Intra-Activity automation, Intra-Sphere automation and Inter-Sphere

automation, illustrated in figure 2. Inter-Activity automation occurs within a particular

process, being somewhat isolated from other processes, whereas Intra-Sphere

automation technologies are a range of interlinked processes, perhaps consisting of an

entire factory or production process, this Kaplinsky feels is the initial differentiating

organisational factor between automation and mechanisation. Inter-Sphere automation

is the final and most complex of these, “Inter-sphere automation is the third and most

complete form of automation and involves coordination between activities in different

spheres of production” (Kaplinsky, 1984, p26). The Caramel lab itself is considered to

be Intra-Sphere automation, with various processes from cooking to drumming

automatically linked; however its incompleteness prevents it from being considered of

Inter-Sphere nature, with automation failing to extend beyond factory walls (Kevin

Oliver, 2003).



Purnell (2000) and Gray (2001) both conclude that automation technologies in food

production bring additional benefits of product quality, improved hygiene and human

benefits. Shane Pugh (2002) claims such benefits are obvious within the Caramel plant,

computer aided sampling ensures products achieve correct grading and less client

refusals, with an incorporated rework tanks allowing for the saviour of incorrect codes.

Shane Pugh (2002) also feels such benefits place huge competitivity gains on

businesses, like most profit maximising organisations Cerestar initially undertook the

Caramel project solely for survival purposes, however nice spin offs matched Bright’s

(1958, p83-84) ideologies including cost reductions, operational improvements,

working environment improvements, product advantages and business pride. When

asked if new technologies make their jobs easier, one hundred per cent of Caramel

respondents agreed, a stark contrast to the 19th Centaury English Textile industry

workers who feared any machine embracement.

“Reduction in required floor supervisors, inspectors, and support personnel, such as

payroll, personnel, food handling and health personnel, can be substantial” (Riley,

1983, p8). There is much argument about the effects upon employment levels

automation yields, although Cerestar did not lose any full time members of staff, they

did experience a slight downsizing through natural wastage of temporary workers.

However, this was nothing comparable to Marx’s view, “technology will create a

massive reserve army of the unemployed” (Jackson, 1998). One notable change was the

contracting out of the drumming process which contributed hugely to this labour

downsizing.



Heathcote (2000, p3) writes “the introduction of technology has led in many instances

to a change in types of job available”, Kevin Oliver (2003) feels not only has the types

of jobs changed, but more specifically the skill requirements. The 1994 OECD jobs

study concluded “Technology both eliminates and creates jobs, generally it destroys

lower wage, lower productivity jobs, while it creates jobs that are more productive,

high-skill and better paid” (South Western College, 2002). However, Bright (1958,

p176) feels such employee upgrading has led to the alienation of unskilled labour

groups, “the automated plant becomes a technological lockout of the common man.

Such a factory will need superskilled specialists, not ordinary labour”. Contradicting

arguments however cite that technology “degradates jobs to the role of button pushers”

(Faunce, 1968), the Caramel questionnaires also reaffirmed this, of 22 respondents,

eighty six percent agreed with Faunce’s statement, however many this felt was purely at

face value of their job.

Do Automation Technologies 'Demote

Jobs to the role of Button Pusher?'

Yes

No



Shane Pugh (2002) refutes such arguments suggesting workers simply require a

different range of expertise rather than reduced ones. Despite this Kevin Oliver (2003)

refers to the modern equivalent job requirements of higher education rather than

traditional apprenticeships served by many modern workforces.

When asked if the new Caramel plant makes their jobs easier, one hundred per cent of

respondents agreed, with ninety five per cent agreeing their job role had changed as a

result. The main focuses of these changes were less physical activities, higher safety

emphasis and more communication. Sixty four per cent of respondents believed

themselves to have gained responsibility, fourteen per cent having lost and twenty two

per cent believing their job to be the same.

New Caramel Plant Responsibility Levels

0

2

4

6

8

10

12

14

16

Gained Lost Same

However, these results are in contrast to Shaiken’s (1981) numerical control study

which indicated that the majority of automation workers had indeed become a slave to

machines (Kaplinsky, 1984, p135). Bright’s (1958, p187) employee-machine theory



also indicates the opposite, stating that although initially automation brings manual

relief, ultimately fixed control and artificial intelligence deprive the user of full control

resulting in job alienation. However, when asked if he felt such technologies had taken

away employee discretion, Kevin Oliver (2003) felt that although in theory they had,

often in practice experienced employees predicted sampling times better than specific

machine calculations. Marcson (1970, p13) and Faunce (1968) both agree with Caramel

lab workers, suggesting that automation promotes a sense of job enlargement and

increased responsibility.

“Perhaps the most widespread statement in automation literature is that the principle

objective for automation is to reduce labour cost. Yet this is only a half-truth.

Underlying most of these situations (Ford, Growmore, Elkhart…) was primarily the

need for more capacity” (Bright 1958, p83). Bright (1958, p170) also writes that new

technologies provide improvements in other areas such as compounding, control and

speed, however Shane Pugh (2002) states that although the new Caramel facility

immediately increased the capacity over the older plant in terms of storage, this didn’t

necessarily imply production increased, although processes can be speeded up and

sampling better perfected, the product still requires appropriate cooking times, referring

back to the overriding reason for the project being business survival. Agreeing with this

Kevin Oliver (2003) believes such large capital investment, $7.5 million, would not be

undertaken simply for negligible capacity increases. Referring to Kaplinsky’s (1984,

p114) ‘0.6 rule’ which implies a direct correlation to investment and capacity, Shane

Pugh (2002) felt that because of such a large range of variables involved it would be

impossible to quantify such gains, however Kevin Oliver (2003) feels the new plant

was a major factor in the acquisition of another major client, Pepsi-Cola.



“In the pre-industrial periods both skilled craftsman and peasants had considerable

control over the rhythms and movements of work. But the machine system now

controls the pace of work and restricts the employee’s free movements” (Marcson,

1970, p13). When asked to state their views on “capitals priority for automation is to

attack those stages of the productive cycle which have the most space for workers to

hold their own pace of work” (Levidow et al, 1981), one hundred per cent of

employees agreed, with a further ninety one per cent agreeing that the new Caramel

plant is also guilty of this.

Does the Caramel Plant force

employees to work at a Computer

Dictated pace?

Yes

No

Shane Pugh (2002) also agrees, stating that most automation systems generally do drive

the operator. However, the caramel plant does suffer patches of inactivity whilst the

product is cooking; followed by a flurry of activity once the computer has indicated

these stages complete.



Marx’s theory of employee alienation is also disputed by Cerestar workers, with the

overwhelmingly positive response to the implementation, sixty eight per cent of

respondents claiming the new technologies live up to their expectations, whereas only

thirty two per cent feel the Caramel plant is below expected standards, citing reasons of

incomplete automation and difficult sampling processes. However, Lindenfeld (1973,

p239) indicates that employees may not actually consciously experience job alienation,

and those that do may simply tolerate this in the face of obvious benefits technology

brings. Despite the overall positive reception, fifty five per cent of workers still feel that

efficiency could have been improved further by utilising complete process automation

of an Inter-Sphere nature.

Retraining was also conducted via shared responsibility between Cerestar and Aston

Dane PLC. With the majority of Caramel Plant workers being in the 46-55 age group,

Marstrand (1984) believes “in a time marked by rapid technological change… it is not

easy for people over fifty to readjust”, Shane Pugh (2002) disputes this, believing

although it isn’t easy, if retraining is conducted in a sympathetic manner making

allowances for computer illiteracy virtually anybody can readjust. He also feels that the

balance of literate and illiterate employees negates any unforeseen problems missed in

training exercises.



Figure 2

The Three Different Types of Automation (Kaplinsky, 1984, p27)

Design Coordination

Manufacture

Automation

(a) Intra-Activity

Automation

Automation

Design Coordination

Manufacture

Automation

(b) Intra-Sphere

Automation

Automation

Design Coordination

Manufacture

(c) Inter-Sphere

Key

Activities

Spheres

Automationtechnologies



Chapter Six: Conclusions

Conclusion: “The result or outcome of an act or process” (yourDictionary, 2003)

Overall from this study it is possible to draw several conclusions. Although automation

is often concerned with the concept of new technology, it is not merely a technological

advancement. Automation is an integrated, harmonious being reliant upon a heavy

balance of variables coming together to promote much greater efficiency than

mechanisation alone. Although there are different types of automation technologies, it

is only Intra-Sphere and Inter-Sphere which truly coin such balanced meaning.

From a capitalist viewpoint, the benefits of such food process reorganisation cannot be

ignored; product quality, improved hygiene, repeatability, operational improvements

and humanity factors all promote and contribute to its uptake. However, automation is

not always critical, as Shane Pugh (2002) states, a corporate image based on

traditionalist methods of production would have little need for implementation.

For employment levels automation can have indifferent effects. Despite much argument

over Marx’s “reserve army of the unemployed” (Jackson, 1998) there is much evidence

that as David Ricardo predicted, technology is a two edged sword. As the 1994 OECD

jobs study concluded, “technology both eliminates and creates jobs” (South Western

College, 2002), destroying lower wage, inhumane, monotonous work whilst eventually

upgrading workers to higher skilled, better paid jobs.



But should this upgrading alienate ordinary man? Studies by Bright (1958, p125) show

contrary to popular belief retraining is not a problem and Shane Pugh (2002) of Aston

Dane PLC believes anybody can be retrained as long as appropriate techniques are

employed. Whether workers want to be retrained is however a different matter, perhaps

automation technologies do demote employees from skilled individual to supervisor,

but is such demotion worthwhile when examining the potential benefits technology

withholds? Would an employee rather operate from within an office or a steamy

ammonia filled factory? As the Caramel questionnaires pointed out, becoming a ‘button

pusher’ is only the face value of a job; computer operations make little difference than

turning dials on machines themselves.

The study also shows other obvious employee benefits, one hundred per cent of

Caramel workers felt that automation technologies had made their job easier, changing

in house focus from simply production to higher safety emphasis, better

communication, better conditions and more regular team meetings. As a result, sixty

four per cent felt automation had promoted more individual responsibility, and as

Marcson (1970, p13) and Faunce (1968) predicted, ultimately brought about job

enlargement. Bright’s (1958, p187) employee-machine relationship theory is also

disproved by Caramel workers, Kevin Oliver (2003) writes that employees often second

guess technology, frequently proving that human discretion produces better results than

machine calculations alone.

Despite the overwhelmingly positive response to the new Caramel plant, Cerestar

employees did agree with both Marcson (1970, p13) and Levidow et al (1981), stating



that such technology has forced them to work at computer dictated pace, although

agreeing in food production timing is always of utmost importance.

Bright (1958, p83) utilising case studies argues that many automation projects are

undertaken not to simply reduce costs through labour and wastage, but often to increase

overall production capacity. However, Shane Pugh (2002) states that although the new

Caramel facility did allow for increased capacity and slight downsizing, these were

certainly not the overriding factors for implementation. Cerestar UK had experienced

increased pressure from its major clients to invest heavily and replace its aging plant,

with the main focus of its implementation being business survival. Kevin Oliver (2003)

however did note a significant increase in production since the new plant, relating this

to Kaplinsky’s (1984, p114) ‘0.6 rule’ from which Cerestar’s investment acquired them

another major client, Pepsi Cola.

Overall the implementation of automation technologies within Cerestar UK’s new

Caramel Production Facility was considered to be a successful project. Aston Dane

PLC feel they “worked hard in bridging the gap between employer’s needs and

employee’s wants from the facility”. The employee’s consensus is they have more

responsibility, more awareness and a better working environment, the employer as a

result is rewarded with increased efficiency, higher production, happier staff and a more

promising future.

In hindsight the methods of data extraction employed in this study provided some

interesting conclusions. Much automation literature remains very unclear and confused,

for every point arguing the benefits of automation technologies, there is always a



contrasting argument. Automation technology is very dependant upon certain variables;

Cerestar’s Caramel plant withholds a certain array of variables which may not be

applicable to another case study. Therefore the overall conclusions to this study maybe

valid in this particular scenario but may not be emulated elsewhere, however without

the use of a case study it would have been impossible to draw accurate or appropriate

conclusions based on literature alone.



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